A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles.

paper Cited Public

Authors: Subramanian, Aravind; Narayan, Rajiv; Corsello, Steven M; Peck, David D; Natoli, Ted E; Lu, Xiaodong; Gould, Joshua; Davis, John F; Tubelli, Andrew A; Asiedu, Jacob K; Lahr, David L; Hirschman, Jodi E; Liu, Zihan; Donahue, Melanie; Julian, Bina; Khan, Mariya; Wadden, David; Smith, Ian C; Lam, Daniel; Liberzon, Arthur; Toder, Courtney; Bagul, Mukta; Orzechowski, Marek; Enache, Oana M; Piccioni, Federica; Johnson, Sarah A; Lyons, Nicholas J; Berger, Alice H; Shamji, Alykhan F; Brooks, Angela N; Vrcic, Anita; Flynn, Corey; Rosains, Jacqueline; Takeda, David Y; Hu, Roger; Davison, Desiree; Lamb, Justin; Ardlie, Kristin; Hogstrom, Larson; Greenside, Peyton; Gray, Nathanael S; Clemons, Paul A; Silver, Serena; Wu, Xiaoyun; Zhao, Wen-Ning; Read-Button, Willis; Wu, Xiaohua; Haggarty, Stephen J; Ronco, Lucienne V; Boehm, Jesse S; Schreiber, Stuart L; Doench, John G; Bittker, Joshua A; Root, David E; Wong, Bang; Golub, Todd R
Year: 2017
Journal: Cell
PMID: 29195078
DOI: 10.1016/j.cell.2017.10.049
PMCID: PMC5990023

Figure 1

L1000 gene expression platform implementation and validationA. Overview of ligation-mediated amplification. Cells are treated in 384-well plates, lysed and mRNA captured on oligo-dT plates. mRNA is reverse-transcribed and oligonucleotide probes designed with transcript-specific, 24-mer unique barcode and universal primer sequences annealed to the cDNA, ligated and PCR-amplified using biotinylated primers. PCR product is hybridized to optically addressed polystyrene microspheres, where each bead is coupled to an oligonucleotide complementary to a landmark gene's barcode. Transcript abundance is quantified by fluorescence using a Luminex FlexMap 3D scanner.B. Deconvoluting 1,000 landmark genes using 500 bead colors. Each bead is analyzed for its bead color (denoting landmark gene identity) and phycoerythrin intensity (denoting transcript abundance). Aliquots of the same bead color, separately coupled to two different gene barcodes, are combined in a ratio of 2:1. A distribution of fluorescent intensities reveals two peaks (partitioned by k-means clustering), the larger peak designating the landmark for which double number of beads were used.C. Validation of L1000 probes using shRNA knockdown. MCF7 and PC3 cells transduced with shRNAs targeting 955 landmark genes. Differential expression values (z-scores) were computed for each landmark and the percentile rank of expression z-scores in the experiment in which it was targeted relative to all other experiments was computed. 841/955 genes (88%) rank in the top 1% of all experiments and 907/955 (95%)rank in the top 5%. Top panel: z-score of BAX gene in every experiment. Middle panel: Z-score distribution from all targeted (orange) and non-targeted (white) genes. Distribution from the targeted set is significantly lower than non-targeted (p value <10-16). Bottom panel: Scatter of percentile rank versus expression z-score for 955 targeted genes.D. Comparison of L1000 with other platforms. Samples of RNA from 6 human cancer cell lines were profiled on L1000, Affymetrix GeneChip HG-U133 Plus 2.0 Array, Illumina Human HT-12 v4 Expression BeadChip Array, and mRNA-seq (Illumina Hi-Seq).E. Comparison of L1000 with RNA-seq and Affymetrix using patient-derived samples. RNA samples from 3,176 tissue specimens profiled on L1000 and RNA-seq, and a subset on Affymetrix microarrays. Top panels: Scatter plots of L1000 expression versus RNA-seq in landmark (left, Spearman correlation of 0.86) and landmark plus inferred (middle, Spearman correlation of 0.91) expression for a single sample. Bottom left:Spearman correlation distribution for L1000 vs RNA-seq of landmark genes for the same sample (orange) and different samples (gray), across all 3,176 patient samples. Bottom right: All L1000 inferred genes were subject to recall analysis by comparison with their RNA-seq measured equivalents. Scatter plot shows R versus cross-platform correlation for all inferred genes. 9,196 of 11,350 (81%) have an R in the 95th percentile (dotted line).

LLM interpretation

This figure consists of five panels (A-E) detailing the implementation and validation of the L1000 gene expression platform. Panels A and B provide schematic diagrams of the ligation-mediated amplification process and the deconvolution of landmark genes using bead colors and fluorescence intensity. Panel C uses a bar chart, density plot, and scatter plot to validate probe specificity via shRNA knockdown, showing a significant shift in z-scores for targeted genes (p < 10⁻¹⁶). Panels D and E utilize a dendrogram and multiple scatter plots to compare L1000 data with RNA-seq and Affymetrix platforms, reporting high Spearman correlations (0.86 to 0.91) and high recall for inferred genes.

Figure 2

L1000 dataset coverage, signature generation, and data accessA. Classification of data in CMap-L1000v1. The 25,200 unique perturbagens correspond to 19,811 compounds, shRNA and/or cDNA targeting 5,075 genes, and 314 biologics. Annotated perturbagens profiled systematically across 9 core cell lines comprise the reference or Touchstone portion of the dataset, while the unannotated reagents make up the Discover portion.B. Modes of access to analysis tools and data. The clue.io software platform enables computational biologists, bench scientists, and software engineers to leverage CMap by offering web applications for analysis, and APIs and docker containers for code and data access.C. Signature generation and data levels. I) Raw bead count and fluorescence intensity measured by Luminex scanners II) Deconvoluted data to assign expression levels to two transcripts measured on the same bead IIIa) Normalization to adjust for non-biological variation IIIb) Inferred expression of 12,328 genes from measurement of 978 landmarks IV) Differential expression values V) Signatures representing collapse of replicate profiles.D. Schematic of query analysis. Query is specified by sets of up- and down-regulated genes. Similarities between the query and all signatures in CMap are computed. Normalized similarities are converted to a p-value and FDR, by comparison with a compendium of random queries, and to τ via comparison with reference signature queries. Perturbagens are then sorted by τ to generate most similar and opposing perturbagens.

LLM interpretation

This figure consists of four panels (A-D) illustrating the L1000 dataset structure, access, processing, and analysis. Panel A is a schematic showing the distribution of 25,200 perturbagens across annotated (Touchstone) and unannotated (Discover) categories. Panel B is a workflow diagram detailing data access via the clue.io platform, APIs, and Docker. Panel C is a linear pipeline showing five data levels (I-V) from raw scans to consensus signatures, and Panel D is a schematic of the query analysis process resulting in a sorted list of similar and opposing perturbagens.

Figure 3

Analysis of genetic loss of function perturbationsA. Off-target effects of shRNAs. Distributions of Spearman correlations between signatures of 12,961 shRNAs in A549 cells targeting the same gene but different seed sequences (blue), targeting different genes but the same seed (red) and all pairs of shRNAs (gray). Distribution was randomly down-sampled to 10 million points. All pairwise comparisons of distributions were significantly different (adjusted p < 10e-7 by Kruskal-Wallis test followed by Dunn test with Benjamini-Hochberg correction).B. Consensus Gene Signature (CGS) improves on-target signal. A consensus gene signature (CGS) is computed from a weighted average of signatures of independent shRNAs targeting the same gene. Connectivity to annotated small molecules targeting each gene (horizontal axis) is markedly improved by CGS over individual shRNAs (with τ closer to 100), suggesting that the CGS procedure mitigates the seed effect inherent to individual shRNAs and enhances on-target signal. Connections are shown summarized across cell lines unless otherwise indicated.C. CRISPR knockout augments compound-target analysis. Top: Consistency between Loss of Function (LoF) signatures from CRISPR and CGS enhances confidence in connectivity to small molecules (CP). Middle: CRISPR-based LoF recovers some connections to small molecules missed by CGS. Bottom: Lack of compound-target connectivity, despite consistency between LoF reagents and validated compound signature suggests non-equivalency of genetic and pharmacological agent-derived signatures.

LLM interpretation

This figure analyzes genetic loss-of-function perturbations across three panels. Panel A is a density plot showing that shRNAs targeting the same gene (blue) have higher Spearman correlations than those sharing the same seed (red) or all pairs (gray), with all distributions significantly different (p < 10e-7). Panel B is a dot plot comparing connectivity scores ($\tau$) of single shRNAs (circles) versus Consensus Gene Signatures (CGS, diamonds) for various gene-inhibitor pairs, showing CGS consistently yields higher connectivity scores closer to 100. Panel C uses a combination of scatter plots and triangular diagrams to compare the connectivity of CGS, CRISPR, and small molecule compounds (CP), illustrating areas of consistency and divergence in their signatures.

Figure 4

Reference perturbagen classes for CMap discoveryA. Process for defining Perturbagen Classes (PCLs). Left: Annotations gathered from literature sources to construct pairwise association matrix between perturbagens based on shared descriptors such as MoA, target gene and pathway membership. Middle: Each perturbagen is subject to ROC analysis to determine whether it recovers expected connections. Right: Remaining members are grouped based on shared annotations and assessed for intra-group connectivity of CMap signatures. Groups sufficiently interconnected are retained as PCLs.B. PCL validation. 137 compounds with known activities corresponding to one or more of 54 PCLs, but not used in PCL construction, were profiled across multiple cell types. Histogram shows rank of each expected PCL connection for the compounds (purple) versus the rank of all unexpected PCL connections (grey). The expected PCL distribution is significantly right-shifted (one-sided p < 2.2e-16 via two-sample KS test).C. Using PCLs for discovery. 3,333 known drugs and 2,418 unannotated but transcriptionally active compounds were subject to PCL analysis. Count of strong and selective connections to validated PCLs byknown drugs (teal) and unannotated compounds (blue). Abbreviations: inh. inhibitor, ag. agonist, rec.receptor, antag. antagonist, and chan. channel.D. Detecting multiple drug activities using PCLs. The PKC inhibitor enzastaurin was profiled in CMap across multiple doses. Connectivity to each established kinase inhibitor PCL is shown in the heatmap. Strong dose-responsive connections were observed to PKC and GSK3 inhibitor PCLs.

LLM interpretation

This figure describes the development and validation of Perturbagen Classes (PCLs) for CMap discovery. Panel A is a workflow diagram showing the process of defining PCLs via literature annotations, ROC analysis, and connectivity assessment; Panel B is a density histogram showing that expected PCL connections (purple) are significantly right-shifted compared to unexpected ones (grey, p < 2.2e-16). Panel C is a horizontal bar chart quantifying the number of known drugs (teal) and unannotated compounds (blue) that strongly connect to various PCLs. Panel D is a heatmap showing the dose-responsive connectivity of the drug enzastaurin to different kinase inhibitor PCLs, with strong connections to PKC and GSK3.

Figure 5

Characterizing known and unexpected activities of small moleculesA. HDAC inhibitor PCL substructure. Hierarchical clustering of pairwise connectivities of the HDAC inhibitor PCL members reveals substructure within the class. Pan-HDAC inhibitors cluster together, distinct from more isoform-selective compounds.B. Antibacterials exhibit lower transcriptional activity than other drugs. Distributions of the maximum TASper compound for 147 antibacterials and 2,372 known drugs in CMap-TS. The antibacterials' TAS distribution is significantly lower (p < 3e-11) than that of other drugs.C. Comparison of unannotated compounds with known drugs. t-SNE projection of the signatures of 2,418unannotated but transcriptionally active compounds (blue) with PCL members (teal). Some unannotated compounds occupy regions not covered by drugs, presenting opportunities for novel chemical development.

LLM interpretation

This figure consists of three panels characterizing small molecule activities. Panel A is a hierarchical clustering heatmap showing pairwise correlations of HDAC inhibitor PCL members, with pan-HDAC inhibitors clustering separately from isoform-selective compounds. Panel B is a box plot comparing transcriptional activity scores (TAS) between antibacterials (n=147) and other drugs (n=2,372), showing significantly lower activity for antibacterials (p < 3e-11). Panel C is a t-SNE projection mapping the signatures of unannotated active compounds (blue) and PCL members (teal), with several labeled clusters identifying specific drug classes such as HDAC, ATPase, and Proteosome inhibitors.

Figure 6

Kinase inhibitor discovery using reference transcriptional signaturesA. Discovery of ROCK1/ROCK2 inhibitor. Top left panel: chemical structure of BRD-2751, predicted to be aROCK inhibitor. Right: TREEspot selectivity profile of Kinomescan binding assay confirmed compound binding to ROCK1/ROCK2. Bottom left: Dose response testing by Kinomescan showed ROCK1 KD of 56 nM.B. Discovery of novel CSNK1A1 inhibitor. Top left panel: The chemical structure of BRD-1868. Top right:TREEspot image of Kinomescan binding assay performed with BRD-1868 at 10 uM demonstrated inhibition of6/456 kinases tested including CSNK1A1. Bottom left: CSNK1A1 binding by BRD-1868 confirmed by Kinomescan, with Kd 2.2 uM. Bottom right: BRD-1868 inhibits phosphorylation of peptide substrate byCSNK1A1, with IC50 12.9 uM. Error bars indicate standard deviation between technical replicates.

LLM interpretation

This figure presents the discovery of two kinase inhibitors, BRD-2751 (A) and BRD-1868 (B), featuring their chemical structures, TREEspot selectivity profiles, and dose-response curves. The TREEspot diagrams use red markers to indicate kinase binding, highlighting ROCK1/ROCK2 for BRD-2751 and CSNK1A1 among others for BRD-1868. Dose-response plots show % control or activity versus log concentration, reporting a $K_d$ of 56 nM for ROCK1 (A), and a $K_d$ of 2.2 $\mu$M and $\text{IC}_{50}$ of 12.9 $\mu$M for CSNK1A1 (B).

Figure 7

Assessing impact of allelic variants and drug response in clinical trialsA. Predicting LoF alleles. Clinically-observed FBXW7 alleles were overexpressed and L1000 profiles obtained. Protein structure shows residues in question. Wild-type FBXW7 connects strongly to MYC shRNA, which is a known target (heat map). Mutations at residues adjacent to the substrate recognition site lose the MYC connection. τ values are summarized across multiple cell types. Bar plot above heat map indicates incidence of each mutation in COSMIC database.B. Interpreting drug resistance. Transcriptional profiles of pre-treatment, early on-treatment, and relapse tumor biopsies obtained from clinical trials of BRAF and MEK inhibitors. Queries from on-treatment versus pre-treatment biopsies exhibited connectivity to pharmacologic inhibition of BRAF or MEK as well as BRAF shRNA in A375 cells, reflecting target engagement in vivo (left 3 columns in heat map). MAP kinase signaling was re-activated, as indicated by a strong negative connection to the same CMap signature in the subset of relapse biopsies with known MAP kinase pathway-related resistance mutations (right 3 columns of heat map).C. Predicting therapeutic efficacy. Transcriptional profiles of pre-treatment and on-treatment biopsies from clinical trial of PHA-793887. Differential expression between the two time points yielded variable connectivity to negative regulators of cell cycle. Patients with strong positive connectivity to cell cycle inhibition signatures remained on trial for a median of 21 weeks; patients with negative connections remained on study for only 8 weeks.

LLM interpretation

This figure consists of three panels (A, B, and C) combining protein structural models, heat maps, and a bar chart to analyze clinical trial data. Panel A shows a 3D protein structure of FBXW7 with highlighted residues, a bar plot of mutation incidence from the COSMIC database, and a heat map showing the connectivity ($\tau$) of various FBXW7 alleles to *MYC* knockdown. Panel B utilizes a heat map to compare transcriptional profiles of pre-treatment, early on-treatment, and relapse biopsies against BRAF and MEK inhibitor signatures. Panel C displays a heat map of connectivity to cell cycle inhibition signatures paired with a horizontal bar chart showing the corresponding duration (weeks) patients remained on a clinical trial.

#	Section	Preview
80	Quantification and Statistical Analysis — L1000 reproducibility using reference mRNA	Samples of purified total RNA from six human cancer cell lines, purchased from Life Technologies,…
81	Quantification and Statistical Analysis — L1000 reproducibility using reference mRNA and cross platform analysis	Samples of purified total RNA from six human cancer cell lines were purchased from Life…
82	Quantification and Statistical Analysis — L1000 reproducibility using shRNAs	The fidelity of L1000 depends on being able to quantify endogenous levels of intended landmark genes…
83	Quantification and Statistical Analysis — L1000 reproducibility using shRNAs	To assess the specificity of L1000 landmark probe measurements, we procured shRNAs that target…
84	Quantification and Statistical Analysis — L1000 reproducibility using shRNAs	The resulting L1000 signature was used to calculate the targeted landmark gene down-regulation and…
85	Quantification and Statistical Analysis — L1000 reproducibility using shRNAs	A probe designed against a landmark gene was progressed if its z-score when targeted by an shRNA was…
86	Quantification and Statistical Analysis — L1000 reproducibility using shRNAs	former was significantly left-shifted, indicating that the observed down-regulation is largely…
87	Quantification and Statistical Analysis — Definition of Recall	An absolute measure of similarity (e.g. Spearman correlation) between samples or genes does not in…
88	Quantification and Statistical Analysis — L1000 comparison to RNA-seq	We sought to compare expression profiles generated using L1000 with those generated using Affymetrix…
89	Quantification and Statistical Analysis — L1000 comparison to RNA-seq	A small subset of these samples were also profiled on Affymetrix, and Figure 1E, top panel, shows…
90	Quantification and Statistical Analysis — L1000 comparison to RNA-seq	To more thoroughly compare L1000 to RNA-seq, we then computed sample self-correlations (using…
91	Quantification and Statistical Analysis — Identifying well inferred genes	We sought to assess the inference quality of the 12,232 features corresponding to inferred-only…
92	Quantification and Statistical Analysis — Gene space summary	The L1000 assay directly measures 978 genes and infers 11,350 more, for a total of 12,328 genes. Of…
93	Quantification and Statistical Analysis — Data preprocessing	The L1000 automated data processing pipeline captures raw data from Luminex scanners as it is…
94	Quantification and Statistical Analysis — Level 1 - Raw (LXB)	Level 1 data comprises the bead identity and raw fluorescent intensity (FI) values measured for…
95	Quantification and Statistical Analysis — Level 2 - Deconvolute (GEX)	The raw FI values associated with each bead color are analyzed in a peak deconvolution step to…
96	Quantification and Statistical Analysis — Level 3 - Normalization (NORM)	In order to reduce artifacts (non-biological sample variation) from the data, we use a rescaling…
97	Quantification and Statistical Analysis — Level 3 - Normalization (NORM)	where x is the unsealed data and a, b, and c are constants estimated empirically. The entire sample…
98	Quantification and Statistical Analysis — Level 3 - Normalization (NORM)	After applying LISS, we standardize the shape of the expression profile distributions on each plate…
99	Quantification and Statistical Analysis — Level 3 - Normalization (NORM)	Normalization yields the expression values of the 978 landmark genes. To obtain expression values…

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An expanded role for single-cell chemical genomics profiling in drug discovery.	Wyatt A et al.	—	2026	→
An integrated drug repositioning analysis identifies rosiglitazone as a treatment for sarcopenia.	Liang S et al.	—	2026	→
APOE-stratified Proteomic and Metabolomic Analysis Reveals Mitochondrial Dysfunction Inflammation and Lipid Dysregulation in Alzheimer's Disease.	Li F et al.	—	2026	→
A precision therapy paradigm for noise-induced hearing loss: integrating transcriptome-guided drug repurposing with <i>in situ</i> hydrogel delivery.	Cai Q et al.	—	2026	→
A prognostic gene model with psychological stress-related genes captures immune activation in breast cancer.	Du T et al.	—	2026	→
Arginine-axis transcriptomics define three neuroblastoma subtypes and a fixed four-gene prognostic signature with immune correlations.	Zheng Y et al.	—	2026	→
Artificial Intelligence in Drug Discovery and Development: Raising Quality per Decision.	Furukawa S et al.	—	2026	→
A screening strategy for identifying the developmental and reproductive toxicity potential of botanicals.	Mahony C et al.	—	2026	→
Benchmarking algorithms for generalizable single-cell perturbation response prediction.	Wei Z et al.	—	2026	→
BiGvCL: bipartite graph-based cross-domain contrastive learning model for the predicting drug-gene interactions.	He S et al.	—	2026	→
CHD4 epigenetically coordinates genomic instability and immunosuppression to drive pan-cancer progression and confer HDAC inhibitor sensitivity.	Fu G et al.	—	2026	→
Computational identification of novel therapeutic candidates for Streptococcus pyogenes and influenza A coinfections through transcriptomic-based drug repositioning.	Strey K et al.	—	2026	→
Computational integration of in vivo single cell and in vitro bulk transcriptomics across 236 human and mouse datasets differentiates physiological versus non-physiological hepatic cell lines for hepatotoxicity screening.	Kowal T et al.	—	2026	→
Context-Specific Genome-Scale Metabolic Modeling to Unravel the Metabolic Rewiring in Human Diseases.	Beura S et al.	—	2026	→
Counting cells can accurately predict small-molecule bioactivity benchmarks.	Seal S et al.	—	2026	→
CRESTA: a comprehensive transcriptome atlas for cellular response to external stressors.	Wang H et al.	—	2026	→
DeepDrugs: a mechanism-aware tri-linear attention framework for synergistic drug-combination prediction.	Xin G et al.	—	2026	→
DeepSTFSynergy: A multi-scale structural information fusion method for personalized drug combination prediction.	Huang Y et al.	—	2026	→
Drug and single-cell gene expression integration identifies sensitive and resistant glioblastoma cell populations.	Suter RK et al.	—	2026	→
Exploring Cutting-Edge Strategies for the Management of Triple-Negative Breast Cancer Through Drug Repurposing.	Chaudhary S et al.	—	2026	→
Exploring the role of circRNA-miRNA-mRNA interactions in cervical cancer progression: insights into HPV status and potential therapeutic approaches.	Sindhu KJ et al.	—	2026	→
Exploring the role of the key gene TNFAIP3 between periodontitis and influenza A through bioinformatic analysis and molecular docking.	Xu M et al.	—	2026	→
Functional implications of polygenic risk for schizophrenia in human neurons.	Michael Deans PJ et al.	—	2026	→
Genetics to Improve Outcomes in Schizophrenia (GENios): A within-case molecular genetic study protocol.	Smart SE et al.	—	2026	→
Genome-wide meta-analyses of non-response to antidepressants provide insights into underlying molecular genetics and suggest potential pharmacotherapies.	Koch E et al.	—	2026	→
GPSAdb 2.0: an expanded atlas of gene-perturbation transcriptomes with enhanced tools for regulatory gene discovery.	Guo S et al.	—	2026	→
Harnessing AI to fuse phenotypic signatures for drug target identification: progress in computational modeling.	Chen F et al.	—	2026	→
Harnessing transcriptomics for discovery of natural products to overcome acquired cancer resistance.	Yeo H et al.	—	2026	→
Hypothesis-driven approach to developmental toxicity assessment: Using mechanistic information to inform testing.	Daston G et al.	—	2026	→
Identification of the immune-related diagnostic biomarkers between Graves' disease and thyroid carcinoma based on comprehensive bioinformatics analysis and machine learning.	Zhu Y et al.	—	2026	→
IFTP-TCM: An ingredient-free explainable framework for target prediction and mechanistic elucidation in traditional Chinese medicine.	Chen F et al.	—	2026	→
Integrative miRNA-mRNA Network and Molecular Dynamics-Based Identification of Therapeutic Candidates for Paroxysmal Nocturnal Hemoglobinuria.	Zhao P et al.	—	2026	→
Integrative transcriptomics and electrophysiological profiling of hiPSC-derived neurons identifies novel druggable pathways in Koolen-de Vries Syndrome.	Verboven AHA et al.	—	2026	→
Interpretation, extrapolation and perturbation of single cells.	Dimitrov D et al.	—	2026	→
Isomeranzin activates Gnas-AMPK signaling to drive white adipose browning and curb obesity in mice.	Shi M et al.	—	2026	→
KORE-Map 1.1: Korean medicine omics resource extension map on transcriptome data of dyspepsia herbal medicine.	Seo EH et al.	—	2026	→
Leveraging the genetics of psychiatric disorders to prioritize potential drug targets and compounds.	Parker N et al.	—	2026	→
Machine learning for drug-target interaction prediction: A comprehensive review of models, challenges, and computational strategies.	Ahmad B et al.	—	2026	→
Multi-ancestry genome-wide association and integrated multi-omics analyses of endometriosis and its clinical manifestations.	Koller D et al.	—	2026	→
Multidimensional transcriptome dataset for systematic evaluation of Jakyakgamcho-tang-induced cell signatures.	Baek SJ et al.	—	2026	→
Multimodal-based analysis of single-cell ATAC-seq data enables highly accurate delineation of clinically relevant tumor cell subpopulations.	Xiong K et al.	—	2026	→
Multi-omic integration identifies broad drug resistance mechanisms and strategies to therapeutically reprogram cancer cells.	Mersich I et al.	—	2026	→
Multi-omics analyses reveal novel metabolic signatures of post-traumatic deep vein thrombosis in patients with coronary heart disease.	Aliyu M et al.	—	2026	→
NADCdb: A Joint Transcriptomic Database for Non-AIDS-Defining Cancer Research in HIV-Positive Individuals.	Xuan J et al.	—	2026	→
Navigating condensate micropolarity to enhance small-molecule drug targeting.	Ouyang J et al.	—	2026	→
Neratinib, a Clinical Drug Treating Breast Cancer, Protects Against Vascular Inflammation and Atherosclerosis.	Zhang FS et al.	—	2026	→
Network-based precision medicine and systems pharmacology.	Pandey AK et al.	—	2026	→
Next-generation precision medicine for pain.	Bhagar R et al.	—	2026	→
Omics-based large language models: A new engine for drug discovery innovation.	Sheng X et al.	—	2026	→
One-hot news: drug synergy models shortcut molecular features.	Çandır EB et al.	—	2026	→
Pan-cancer gene signature analysis of macrophage polarization and compound prediction for reprogramming tumor-associated macrophages toward M1-like macrophages.	Liu X et al.	—	2026	→
Pathogenomic analysis reveals clinically relevant epithelial-mesenchymal plasticity in esophageal squamous cell carcinoma.	Chen R et al.	—	2026	→
Pertpy: an end-to-end framework for perturbation analysis.	Heumos L et al.	—	2026	→
Pharmaco-behavioral profiling identifies suppressors of autism gene-associated phenotypes in zebrafish.	Jamadagni P et al.	—	2026	→
Pharmacotranscriptomics-based discovery and hydrogel-mediated delivery of drug combinations for potentiated cancer immunotherapy.	Liu R et al.	—	2026	→
Photoaffinity Labeling Strategy Reveals Tetraspanin CD9 as a Transient Target of Anticancer Yaku'amide B.	Fu J et al.	—	2026	→
Potent and selective LSD1 inhibitor DC551040 reveals a promising combination therapy for AML with insight into epigenetic dysregulation.	Wang J et al.	—	2026	→
Predicting condition-aware drug-induced transcriptional responses via a latent diffusion model.	Kim C et al.	—	2026	→
Predicting drug-perturbed transcriptional responses using multi-conditional diffusion transformer.	Hu Q et al.	—	2026	→
Proteome-wide multi-trait association analyses prioritize candidate proteins and therapeutic targets for psychiatric disorders.	Yao S et al.	—	2026	→
Purvalanol A Exerts Anti-Hepatocellular Carcinoma Activity by Activating the p53 Pathway.	Yang Y et al.	—	2026	→
scLong: a billion-parameter foundation model for capturing long-range gene context in single-cell transcriptomics.	Bai D et al.	—	2026	→
SDMap: a comprehensive database of spatial drug perturbation maps.	Li F et al.	—	2026	→
Selective inhibition of ALDH1A3 impedes breast cancer growth and metastasis by blocking ALDH1A3-driven transcriptional programs.	MacLean MR et al.	—	2026	→
SiCmiR Atlas: Single-Cell miRNA Landscape Reveals Hub-miRNA and Network Signatures in Human Cancers.	Cai XX et al.	—	2026	→
Silencer variants are key drivers of gene up-regulation in Alzheimer's disease.	Huang D et al.	—	2026	→
Single-Cell Lineage Tracing Uncovers Resistance Signatures and Sensitizing Strategies to FLT3 Inhibitors in Acute Myeloid Leukemia.	Eriksson J et al.	—	2026	→
Sotatercept for the treatment of portopulmonary hypertension: a case report.	Jose A et al.	—	2026	→
Spatial transcriptomics reveals a key role of fibroblast-like vascular smooth muscle cells in human atherosclerotic cell crosstalk and stability.	Goncalves I et al.	—	2026	→
Targeting Mitochondrial Stress Responses: Terbinafine and Miglustat as Novel Lifespan and Healthspan Modulators.	Lalou A et al.	—	2026	→
Targeting TPX2-dependent lineage plasticity by CDK4/6 inhibition reverses therapy resistance in neuroendocrine bladder carcinoma.	Chen Z et al.	—	2026	→
The anoikis signature in rheumatoid arthritis: Insights into methotrexate resistance and the complementary therapeutic role of triptolide.	Zhang Y et al.	—	2026	→
The brain neurovascular epigenome and its association with dementia.	Ziegler KC et al.	—	2026	→
The CFDE Workbench: Integrating Metadata and Processed Data from Common Fund Programs.	Evangelista JE et al.	—	2026	→
Therapeutic target database 2026: facilitating targeted therapies and precision medicine.	Zhang Y et al.	—	2026	→
Transcriptomic Analysis of the Amygdala in Subjects with Schizophrenia, Bipolar Disorder and Major Depressive Disorder Reveals Differentially Altered Metabolic Pathways.	Zhang X et al.	—	2026	→
Transcriptomic and phenotypic convergence of neurodevelopmental disorder risk genes in vitro and in vivo.	Fernandez Garcia M et al.	—	2026	→
Transitive prediction of small-molecule function through alignment of high-content screening resources.	Bao F et al.	—	2026	→
Trichothecene mycotoxin-induced ribotoxic stress activates histone gene transcription.	Kolb AF et al.	—	2026	→
Trimetazidine modulates angiogenesis, inflammation, and metabolism-related gene expression to promote diabetic foot ulcer healing: a transcriptomic analysis.	Dulcic D et al.	—	2026	→
4D marmoset brain map reveals MRI and molecular signatures for onset of multiple sclerosis-like lesions.	Lin JP et al.	—	2025	→
4-Hydroxychalcone Inhibits Human Coronavirus HCoV-OC43 by Targeting EGFR/AKT/ERK1/2 Signaling Pathway.	Huang Y et al.	—	2025	→
A bibliometric analysis and systematic review of drug repurposing against drug-resistant ESKAPE pathogens: a particular focus on <i>Pseudomonas aeruginosa</i>.	Guo S et al.	—	2025	→
Abnormal global longitudinal strain and reduced serum inflammatory markers in cardiac AL amyloidosis patients without significant amyloid fibril deposition.	Edwards CV et al.	—	2025	→
A clinical road map for single-cell omics.	Skinnider MA et al.	—	2025	→
A comparative analysis of Marburg virus-infected bat and human models from public high-throughput sequencing data.	Xuan DTM et al.	—	2025	→
A comparison of computational methods for expression forecasting.	Kernfeld E et al.	—	2025	→
A computational genetic- and transcriptomics-based study nominates drug repurposing candidates for the treatment of chronic pain.	Cote AC et al.	—	2025	→
Acquisition, quality control, and architecture of a large image dataset as a tool for in silico cell biological research.	Konshin N et al.	—	2025	→
Active learning framework leveraging transcriptomics identifies modulators of disease phenotypes.	DeMeo B et al.	—	2025	→
A cycling, progenitor-like cell population at the base of atypical teratoid rhabdoid tumor subtype differentiation trajectories.	Blanco-Carmona E et al.	—	2025	→
Adaptive multi-view learning method for enhanced drug repurposing using chemical-induced transcriptional profiles, knowledge graphs, and large language models.	Yan Y et al.	—	2025	→
A deep generative model for deciphering cellular dynamics and in silico drug discovery in complex diseases.	Zheng Y et al.	—	2025	→
A deep learning framework for <i>in silico</i> screening of anticancer drugs at the single-cell level.	Zhang P et al.	—	2025	→
Advances and Challenges in Drug Screening for Cancer Therapy: A Comprehensive Review.	Motohashi S et al.	—	2025	→
Advances in Computational Drug Repurposing, Driver Genes, and Therapeutics in Lung Adenocarcinoma.	Nematzadeh S et al.	—	2025	→
Advances in high-throughput drug screening based on pharmacotranscriptomics.	Qiao L et al.	—	2025	→
Advancing PROTAC Discovery Through Artificial Intelligence: Opportunities, Challenges, and Future Directions.	Park KS et al.	—	2025	→
Advancing toxicity AI-based prediction with multilevel systems biology: a case study on genotoxicity.	Zhang X et al.	—	2025	→
Age-Dependent Regulation of Hippocampal Inflammation by the Mitochondrial Translocator Protein in Mice.	Lai KO et al.	—	2025	→
A genotype-to-drug diffusion model for generation of tailored anti-cancer small molecules.	Kim H et al.	—	2025	→
A graph neural network approach for hierarchical mapping of breast cancer protein communities.	Zhang X et al.	—	2025	→
A graph neural network-based approach for predicting SARS-CoV-2-human protein interactions from multiview data.	Ray S et al.	—	2025	→
A guide for active learning in synergistic drug discovery.	Wang S et al.	—	2025	→
A human metabolic map of pharmacological perturbations reveals drug modes of action.	Schuhknecht L et al.	—	2025	→
AI-enabled drug prediction and gene network analysis reveal therapeutic use of vorinostat for Rett Syndrome in preclinical models.	Novak R et al.	—	2025	→
Altered immune response is associated with sex difference in vulnerability to Alzheimer's disease in human prefrontal cortex.	Wen H et al.	—	2025	→
A Machine-Learning Approach Identifies Rejuvenating Interventions in the Human Brain.	Santamaria G et al.	—	2025	→
A Machine Learning Approach to Molecular Initiating Event Prediction Using High-Throughput Transcriptomic Chemical Screening Data.	Bundy JL et al.	—	2025	→
A machine learning-derived immune-related prognostic model identifies <i>PLXNA3</i> as a functional risk gene in colorectal cancer.	Lyu H et al.	—	2025	→
A multimodule graph-based neural network for accurate drug-target interaction prediction via genomic, proteomic, and structural data fusion.	Maryam et al.	—	2025	→
A multiomic atlas identifies a treatment-resistant, bone marrow progenitor-like cell population in T cell acute lymphoblastic leukemia.	Xu J et al.	—	2025	→
A multiplex single-cell RNA-Seq pharmacotranscriptomics pipeline for drug discovery.	Dini A et al.	—	2025	→
Analysis of Different Strains of the Turquoise Killifish Identify Transcriptomic Signatures Associated With Heritable Lifespan Differences.	Mazzetto M et al.	—	2025	→
An Application of a Large-Scale, Data-Driven Approach to Prioritize Compound-Targeted Conditions in the Nutraceutical Space: Case Study of Quercefit<sup>TM</sup> (Quercetin Phytosome) Toward Unbalanced Lipid Conditions in Metabolically Challenged Adults.	Lili L et al.	—	2025	→
An atlas of single-cell eQTLs dissects autoimmune disease genes and identifies novel drug classes for treatment.	Wang L et al.	—	2025	→
AnchorDrug: A system for drug-induced gene expression prediction in new contexts through active learning.	Meng H et al.	—	2025	→
An Immune Subtype Classification System Enables the Development of Strategies to Predict and Enhance Immunotherapy Responses in Colorectal Cancer.	Li D et al.	—	2025	→
An induced pluripotent stem cell-based chemical genetic approach for studying spinal muscular atrophy.	Giadone RM et al.	—	2025	→
An integrated proteomic portrait of prostate cancer progression.	Zhang J et al.	—	2025	→
An Integrative Drug-Induced Transcriptomic Analysis Identifies Novel MYC Antagonists and Potential Synergistic Drug Combinations.	Aceto A et al.	—	2025	→
Anomaly detection for high-content image-based phenotypic cell profiling.	Shpigler A et al.	—	2025	→
Anticancer effects and mechanisms of <i>Pulsatilla chinensis</i>, <i>Bupleurum chinense</i> and <i>Polyporus umbellatus</i> on human lung carcinoma and hepatoma cells.	Li M et al.	—	2025	→
Anticancer Monotherapy and Polytherapy Drug Response Prediction Using Deep Learning: Guidelines and Best Practices.	Emad A et al.	—	2025	→
A pan-cancer analysis of homeobox family: expression characteristics and latent significance in prognosis and immune microenvironment.	Wang Y et al.	—	2025	→
[A pan-cancer analysis of PYCR1 and its predictive value for chemotherapy and immunotherapy responses in bladder cancer].	Li Y et al.	—	2025	→
APOE ε4 allele drives female-specific Alzheimer's disease progression via vascular dysfunction and tau spreading.	Huang S et al.	—	2025	→
Apoptotic signatures allow early and rapid screening of drug-induced liver injury to accelerate drug discovery.	Hellgren J et al.	—	2025	→
Application of GWAS summary data and drug-induced gene expression profiles of neural progenitor cells in psychiatric drug prioritization analysis.	Li X et al.	—	2025	→
Applications of Artificial Intelligence in Drug Repurposing.	Wan Z et al.	—	2025	→
Arterial-Lymphatic-Like Endothelial Cells Appear in Hereditary Hemorrhagic Telangiectasia 2 and Contribute to Vascular Leakage and Arteriovenous Malformations.	Yang Y et al.	—	2025	→
Artificial Clinic Intelligence (ACI): A Generative AI-Powered Modeling Platform to Optimize Patient Cohort Enrichment and Clinical Trial Optimization.	Ung CY et al.	—	2025	→
Artificial intelligence and anti-cancer drugs' response.	Long X et al.	—	2025	→
Assessing the impact of in vitro xenobiotic metabolism on estrogenic chemical bioactivity in high-throughput profiling assays.	Jurgelewicz A et al.	—	2025	→
Assessment of chemical risk factor for breast cancer based on gene expression profiles.	Achebouche R et al.	—	2025	→
A survey on deep learning for drug-target binding prediction: models, benchmarks, evaluation, and case studies.	Debnath K et al.	—	2025	→
A Transfer Learning Framework for Predicting and Interpreting Drug Responses via Single-Cell RNA-Seq Data.	He Y et al.	—	2025	→
Aurora kinase B inhibitor AZD1152: repurposing for treatment of lupus nephritis driven by the results of clinical trials.	Zhao Y et al.	—	2025	→
Automated High-Content, High-Throughput Spatial Analysis Pipeline for Drug Screening in 3D Tumor Spheroid Inverted Colloidal Crystal Arrays.	Jeon H et al.	—	2025	→
A versatile information retrieval framework for evaluating profile strength and similarity.	Kalinin AA et al.	—	2025	→
AΙ-Driven Drug Repurposing: Applications and Challenges.	Keramida P et al.	—	2025	→
BADGER: biologically-aware interpretable differential gene expression ranking model.	Kim H et al.	—	2025	→
Benchmarking foundation cell models for post-perturbation RNA-seq prediction.	Csendes G et al.	—	2025	→
Benchmarking of dimensionality reduction methods to capture drug response in transcriptome data.	Kwon Y et al.	—	2025	→
Calbindin 2 as a Novel Biomarker and Therapeutic Target for Abdominal Aortic Aneurysm: Integrative Analysis of Human Proteomes and Genetics.	Bao Y et al.	—	2025	→
Capturing disease severity in LIS1-lissencephaly reveals proteostasis dysregulation in patient-derived forebrain organoids.	Zillich L et al.	—	2025	→
Causal models and prediction in cell line perturbation experiments.	Long JP et al.	—	2025	→
Celecoxib Enhances Oxidative Muscle Fibre Formation and Improves Muscle Functions Through Prokr1 Activation in Mice.	Park JH et al.	—	2025	→
Cell morphology and gene expression: tracking changes and complementarity across time and cell lines.	Lejal V et al.	—	2025	→
Cell type and region-specific transcriptional changes in the endometrium of women with RIF identify potential treatment targets.	Tempest N et al.	—	2025	→
Chemical reprogramming of fibroblasts into retinal pigment epithelium cells for vision restoration.	Li S et al.	—	2025	→
Chemokine-like factor-like MARVEL transmembrane domain-containing 1 identified as a novel target protein for immune dysregulation in sepsis: A machine learning and molecular dynamics framework for diagnostic biomarkers and therapeutic exploration.	Lin J et al.	—	2025	→
Combining mitochondrial proteomes and Mendelian randomization to identify novel therapeutic targets for diabetic nephropathy.	Liu Y et al.	—	2025	→
Comparative analysis of regression algorithms for drug response prediction using GDSC dataset.	Ha S et al.	—	2025	→
Comparative and pharmacological investigation of bEVs from eight Lactobacillales strains.	Park S et al.	—	2025	→
Comprehensive analysis of high-throughput transcriptomics to distinguish drug-induced liver injury (DILI) phenotypes.	Shin S et al.	—	2025	→
Comprehensive bioinformatic analysis identifies potential therapeutic drugs for CryAB (R120G)-related cardiomyopathy.	Zheng J et al.	—	2025	→
Comprehensive characterization of fatty acid oxidation in triple-negative breast cancer: Focus on biological roles and drug modulation.	Liu Y et al.	—	2025	→
Comprehensive evaluation of pure and hybrid collaborative filtering in drug repurposing.	Réda C et al.	—	2025	→
Comprehensive Proteomics Metadata and Integrative Web Portals Facilitate Sharing and Integration of LINCS Multiomics Data.	Vidović D et al.	—	2025	→
Computational Drug Repositioning in Cardiorenal Disease: Opportunities, Challenges, and Approaches.	Perco P et al.	—	2025	→
Computational Drug Repurposing Across the Multiple Myeloma Spectrum: From MGUS to MM.	Savva K et al.	—	2025	→
Computational drug repurposing: approaches, evaluation of in silico resources and case studies.	Tanoli Z et al.	—	2025	→
Computational framework for prioritizing candidate compounds overcoming the resistance of pancancer immunotherapy.	Feng F et al.	—	2025	→
Computational Insights into the Polypharmacological Landscape of BCR-ABL Inhibitors: Emphasis on Imatinib and Nilotinib.	Hajjo R et al.	—	2025	→
Connectivity mapping with isotretinoin's transcriptomic signature identifies alternative therapeutics for severe acne.	Sennett ML et al.	—	2025	→
Connectivity-map unveils Gemcitabine's efficacy in overcoming nelarabine resistance in T-cell acute lymphoblastic leukemia.	Ximei Wu et al.	—	2025	→
Construction of Metastasis Prediction Models and Screening of Anti-Metastatic Drugs Based on Pan-Cancer Single-Cell EMT Features.	Xu Y et al.	—	2025	→
CORN 2.0 - Condition Orientated Regulatory Networks 2.0.	Leung RWT et al.	—	2025	→
CREBBP Mutation as a Culprit for Negative SSTR2 PET in Neuroendocrine Tumors.	Haj-Mirzaian A et al.	—	2025	→
CRISPR targeting of FOXL2 c.402C>G mutation reduces malignant phenotype in granulosa tumor cells and identifies anti-tumoral compounds.	Amarilla-Quintana S et al.	—	2025	→
cSTAR analysis identifies endothelial cell cycle as a key regulator of flow-dependent artery remodeling.	Deng H et al.	—	2025	→
Data-driven drug repositioning using olfactory omics profiles: challenges and perspectives in neurodegeneration.	Cartas-Cejudo P et al.	—	2025	→
Data-driven strategies for drug repurposing: insights, recommendations, and case studies.	Savander S et al.	—	2025	→
Deciphering direct transcriptional effects of epigenetic compounds through large-scale new RNA profiling.	Hartmanis L et al.	—	2025	→
Decoding cell fate: integrated experimental and computational analysis at the single-cell level.	Zhou Y et al.	—	2025	→
Decrypting the molecular basis of cellular drug phenotypes by dose-resolved expression proteomics.	Eckert S et al.	—	2025	→
Deep generative modeling of sample-level heterogeneity in single-cell genomics.	Boyeau P et al.	—	2025	→
De novo pyrimidine biosynthesis inhibition synergizes with BCL-X<sub>L</sub> targeting in pancreatic cancer.	Zhang H et al.	—	2025	→
Developing a novel aging assessment model to uncover heterogeneity in organ aging and screening of aging-related drugs.	Xu Y et al.	—	2025	→
Development and application of meta-analysis in environmental health research.	Li Q et al.	—	2025	→
Development of a prognostic prediction signature for idiopathic pulmonary fibrosis by integrating multiple programmed cell death-related genes and machine learning algorithms.	Sun J et al.	—	2025	→
DGSS: A Dynamic Interaction Graph Neural Network with Specific Substructure Awareness for Drug Synergy Prediction.	Ge J et al.	—	2025	→
Digital twins in healthcare: a comprehensive review and future directions.	Khoshfekr Rudsari H et al.	—	2025	→
Dimethyl fumarate is repurposed to ameliorate aortic aneurysm and dissection in mice.	Wang X et al.	—	2025	→
DIORS: Enhancing drug-target interaction prediction via structure and signature integrated-driven approach and discovering potential targeted molecules.	Tang Y et al.	—	2025	→
Discovering anticancer drug target combinations via network-informed signaling-based approach.	Yavuz BR et al.	—	2025	→
Discovery of TBK1-Associated Oncogenic Mechanisms in Patients With Upper Tract Urothelial Carcinoma and Pre-Existing End-Stage Renal Disease.	Huang YP et al.	—	2025	→
DLK1 Distinguishes Subsets of NF1-Associated Malignant Peripheral Nerve Sheath Tumors with Divergent Molecular Signatures.	Mitchell DK et al.	—	2025	→
DOSE-L1000-Viz: an interactive Shiny application for dose-response transcriptomic analysis, target-centric exploration, and signature search.	Wang J	—	2025	→
Drug-induced cytotoxicity prediction in muscle cells, an application of the Cell Painting assay.	Lambert R et al.	—	2025	→
Drug-induced liver injury prediction based on graph convolutional networks and toxicogenomics.	Xiao T et al.	—	2025	→
Drug Repositioning Based on Cerebrospinal Fluid Proteomes Using Connectivity Map Framework.	Cortés A et al.	—	2025	→
Drug repositioning based on mutual information for the treatment of Alzheimer's disease patients.	Cava C et al.	—	2025	→
Drug Repositioning for HPV Clade-Specific Cervicouterine Cancer Using the OCTAD Pipeline.	Ruiz-Hernández J et al.	—	2025	→
Drug repositioning for pan-cancers of the digestive system: Identification of amonafide and BX795 as potential therapeutics via integrative Omics analysis.	Liu W et al.	—	2025	→
Drug repurposing for non-small cell lung cancer by predicting drug response using pathway-level graph convolutional network.	Anjusha IT et al.	—	2025	→
Drug repurposing in amyotrophic lateral sclerosis (ALS).	Carroll E et al.	—	2025	→
Drug Search and Design Considering Cell Specificity of Chemically Induced Gene Expression Profiles for Disease-Associated Tissues.	Yamanaka C et al.	—	2025	→
Dual-Algorithm Integration Framework Reveals Qing-Wei-Zhi-Tong's Dual Mechanisms in Chronic Gastritis.	Shu Z et al.	—	2025	→
Edaravone targets PDGFRβ to attenuate VSMC phenotypic transition.	Tang X et al.	—	2025	→
Efferocytosis-related signatures identified via Single-cell analysis and machine learning predict TNBC outcomes and immunotherapy response.	Wei L et al.	—	2025	→
Elucidating Pancreatic Ductal Adenocarcinoma Carcinogenesis at Single-Cell Resolution and Identifying Subtype Specific Drug Candidates.	Chen J et al.	—	2025	→
Emerging roles of the cancerous inhibitor of protein phosphatase 2A (CIP2A) in ovarian cancer.	Filipe A et al.	—	2025	→
Epigene functional diversity: isoform usage, disordered domain content, and variable binding partners.	Bondhus L et al.	—	2025	→
Establishment of interpretable cytotoxicity prediction models using machine learning analysis of transcriptome features.	Wu Y et al.	—	2025	→
Estimating progression of Alzheimer's disease with extracellular vesicle-related multi-omics risk models.	Zhang X et al.	—	2025	→
Evaluating current status of network pharmacology for herbal medicine focusing on identifying mechanisms and therapeutic effects.	Lee WY et al.	—	2025	→
Evaluation of large language models for discovery of gene set function.	Hu M et al.	—	2025	→
Exploiting similarity in drug molecular effects for drug repurposing.	Huang K et al.	—	2025	→
Exploration of a prognostic signature for mitochondria-related genes and the therapeutic prospects of vorinostat in clear cell renal cell carcinoma.	Li W et al.	—	2025	→
Exploration of oxidative stress-mediated genetic toxicology modes of action using a pathway analysis, Connectivity Mapping, and transcriptional benchmark dosing-based framework.	De Abrew KN et al.	—	2025	→
Exploring biomarkers and molecular mechanisms of Type 2 diabetes mellitus promotes colorectal cancer progression based on transcriptomics.	Luo S et al.	—	2025	→
Exploring molecular and modular insights into space ionizing radiation effects through heterogeneous gene regulatory networks.	Yuan M et al.	—	2025	→
Exploring the association between DNA methylation and pancreatic cancer susceptibility through epigenome-wide Mendelian randomization and multi-omics data integration.	Wang P et al.	—	2025	→
Exploring the Impact of Microgravity on Gene Expression: Dysregulated Pathways and Candidate Repurposed Drugs.	Galčenko K et al.	—	2025	→
Exploring the omnigenic architecture of selected complex traits.	Ratajczak F et al.	—	2025	→
Exploring the shared molecular mechanisms of primary hypertension and IgA vasculitis through a case report and combining bioinformatics analysis.	Wei Q et al.	—	2025	→
Exploring WNT pathway dysregulation in serrated colorectal cancer for improved diagnostic and therapeutic strategies.	Zhu F et al.	—	2025	→
Extracellular vesicle-associated transcriptomic and proteomic biomarkers show in vitro potential for vandetanib treatment monitoring in anaplastic thyroid cancer.	Grätz C et al.	—	2025	→
Extracellular vesicles as a promising tool in neuropsychiatric pharmacotherapy application and monitoring.	Balic N et al.	—	2025	→
FADS2 and ALDOC as potential adipose tissue biomarkers in obesity: responses to low-calorie diet-feeding.	Chen S et al.	—	2025	→
Ferroptosis-related genes participate in the microglia-induced neuroinflammation of spinal cord injury via NF-κB signaling: evidence from integrated single-cell and spatial transcriptomic analysis.	Wang S et al.	—	2025	→
Folding-Based End-To-End Chemical Drug Design with Uncertainty Estimation: Tackling Hallucination in the Post-GPT Era.	Zhong F et al.	—	2025	→
FOSB is a key factor in the genetic link between inflammatory bowel disease and acute myocardial infarction: multiple bioinformatics analyses and validation.	Fu Q et al.	—	2025	→
From Gene Networks to Therapeutics: A Causal Inference and Deep Learning Approach for Drug Discovery.	Ghandikota S et al.	—	2025	→
From matrix factorization to graph neural networks: Advances in computational drug repositioning.	Wang Y et al.	—	2025	→
From rare to more common: The emerging role of omics in improving understanding and treatment of severe inflammatory and hyperinflammatory conditions.	Keskitalo S et al.	—	2025	→
Functional recovery of islet β cells in human type 2 diabetes: Transcriptome signatures unveil therapeutic approaches.	Suleiman M et al.	—	2025	→
Gene expression inference based on graph neural networks using L1000 data.	Kim TH et al.	—	2025	→
Gene expression signatures from whole blood predict amyotrophic lateral sclerosis case status and survival.	Zhao Y et al.	—	2025	→
Gene Signature-Based Drug Screening Reveals Ponatinib Enhances Immunotherapy Efficacy in Triple-Negative Breast Cancer by Reversing MDSC-Mediated Immunosuppressive Tumor Microenvironment.	Wang Q et al.	—	2025	→
Genetically Proxied Antiplatelet Drug Target Perturbation and Risk of Aneurysmal Subarachnoid Hemorrhage: A Mendelian Randomization Analysis.	Fan YX et al.	—	2025	→
Genetic Studies Through the Lens of Gene Networks.	Subirana-Granés M et al.	—	2025	→
Glucocorticoid promotes metastasis of colorectal cancer via co-regulation of glucocorticoid receptor and TET2.	Song Y et al.	—	2025	→
GPX3 as a Novel and Potential Therapeutic Target in the Shared Molecular Mechanisms of Traumatic Brain Injury and Parkinson's Disease.	Wang Y et al.	—	2025	→
GramSeq-DTA: A Grammar-Based Drug-Target Affinity Prediction Approach Fusing Gene Expression Information.	Debnath K et al.	—	2025	→
Graph based recurrent network for context specific synthetic lethality prediction.	Jiang Y et al.	—	2025	→
Gut Microbiota Mediate Periampullary Cancer Through Extracellular Matrix Proteins: A Causal Relationship Study.	Cheng Z et al.	—	2025	→
Harnessing Single-Cell RNA-Seq for Computational Drug Repurposing in Cancer Immunotherapy.	Cheng OJ et al.	—	2025	→
HDAC inhibitors engage MITF and the disease-associated microglia signature to enhance amyloid β uptake.	Haage V et al.	—	2025	→
HERB 2.0: an updated database integrating clinical and experimental evidence for traditional Chinese medicine.	Gao K et al.	—	2025	→
High-throughput profiling of chemical-induced gene expression across 93,644 perturbations.	Xiang L et al.	—	2025	→
HSP90 co-regulates the formation and nuclear distribution of the glycolytic output complex to promote resistance and poor prognosis in gastric cancer patients.	Shen G et al.	—	2025	→
Hyperbolic Nature of Differential Expression Signatures.	Pogany D et al.	—	2025	→
Icariside II inhibits Epithelial-Mesenchymal transition in metastatic osteosarcoma by antagonizing the miR-194/215 cluster via PGK1.	Hu J et al.	—	2025	→
Identification and Experimental Validation of NETosis-Mediated Abdominal Aortic Aneurysm Gene Signature Using Multi-omics, Machine Learning, and Mendelian Randomization.	Wu C et al.	—	2025	→
Identification and exploration of novel biomarkers and potential therapeutic agents for the progression of sepsis to septic ARDS.	Chen H et al.	—	2025	→
Identification and Validation of Antidepressant Small Molecules Using Bioinformatics and Mouse Depression Models.	Qiao Y et al.	—	2025	→
Identification and Validation of the Key Genes of Diabetic Vasculopathy: Evidence Based on Bioinformatics Analysis and Animal Study.	Li F et al.	—	2025	→
Identification and verification of mitochondria-related genes biomarkers associated with immune infiltration for COPD using WGCNA and machine learning algorithms.	Peng M et al.	—	2025	→
Identification of an Amino Acid Metabolism Reprogramming Signature for Predicting Prognosis, Immunotherapy Efficacy, and Drug Candidates in Colon Cancer.	Du F et al.	—	2025	→
Identification of a PRDM1-regulated T cell network to regulate atherosclerotic plaque inflammation.	Jin H et al.	—	2025	→
Identification of compounds to promote diabetic wound healing based on transcriptome signature.	Shang J et al.	—	2025	→
Identification of critical endoplasmic reticulum stress-related genes in advanced atherosclerotic plaque.	Zhao N et al.	—	2025	→
Identification of diabetes-related signatures as prognostic and therapeutic biomarkers in colon cancer.	Yao M et al.	—	2025	→
Identification of gene signatures and potential pharmaceutical candidates linked to COVID-19-related depression based on gene expression profiles.	Chen S et al.	—	2025	→
Identification of key genes in pancreatic ductal adenocarcinoma with biologically informed deep neural network.	Gao R et al.	—	2025	→
Identification of key modules and hub genes for sepsis-induced myopathy using weighted gene co-expression network analysis.	Lin S et al.	—	2025	→
Identification of natural product-based drug combination (NPDC) using artificial intelligence.	Niu T et al.	—	2025	→
Identification of potential natural compounds to relieve deoxynivalenol-induced intestinal damage based on bioinformatics and reverse network pharmacology.	Li R et al.	—	2025	→
Identification of the immune infiltration and biomarkers in ulcerative colitis based on liquid-liquid phase separation-related genes.	Hong Z et al.	—	2025	→
Identifying Age-Modulating Compounds Using a Novel Computational Framework for Evaluating Transcriptional Age.	Zhang C et al.	—	2025	→
Identifying compounds to treat opiate use disorder by leveraging multi-omic data integration and multiple drug repurposing databases.	Stratford JK et al.	—	2025	→
Identifying Lactylation-related biomarkers and therapeutic drugs in ulcerative colitis: insights from machine learning and molecular docking.	Yang Y et al.	—	2025	→
Identifying potential co-expressed genes and molecular mechanisms linking post-COVID-19 and Guillain-Barre syndrome through neutrophil extracellular trap-related genes.	Su JH et al.	—	2025	→
IGFBP3-mediated effects of an effective combination therapy on HCC.	Chen L et al.	—	2025	→
IL-33 is associated with alveolar dysfunction in patients with viral lower respiratory tract disease.	Scott IC et al.	—	2025	→
Image2Reg: Linking chromatin images to gene regulation using genetic and chemical perturbation screens.	Paysan D et al.	—	2025	→
Immune-related glycosylation genes based classification predicts prognosis and therapy options of osteosarcoma.	Wang W et al.	—	2025	→
Impact of Y chromosome loss on the risk of Parkinson's disease and progression.	Wang J et al.	—	2025	→
Improving synergistic drug combination prediction with signature-based gene expression features in oncology.	Mozaffarilegha M et al.	—	2025	→
Incorporating Metabolic Competence into High-Throughput Profiling Assays.	Jurgelewicz A et al.	—	2025	→
Inhibition of FOXM1 Synergizes with BH3 Mimetics Venetoclax and Sonrotoclax in Killing Multiple Myeloma Cells through Repressing MYC Pathway.	Wen Z et al.	—	2025	→
Inhibition of Thioredoxin-Reductase by Auranofin as a Pro-Oxidant Anticancer Strategy for Glioblastoma: In Vitro and In Vivo Studies.	Chmelyuk N et al.	—	2025	→
In Search of Molecular Correlates of Fibromyalgia: The Quest for Objective Diagnosis and Effective Treatments.	Bonomi S et al.	—	2025	→
Insights, opportunities, and challenges provided by large cell atlases.	Hemberg M et al.	—	2025	→
In silico biological discovery with large perturbation models.	Miladinovic D et al.	—	2025	→
In silico drug sensitivity predicts subgroup-specific therapeutics in medulloblastoma patients.	Jermakowicz AM et al.	—	2025	→
Integrated Analysis of Proteome and Transcriptome Profiling Reveals Pan-Cancer-Associated Pathways and Molecular Biomarkers.	Hu GS et al.	—	2025	→
Integrated Bioinformatics Analyses of Peripheral Blood Transcriptomes Reveals Shared Molecular Features Underlying the Comorbidity of Schizophrenia and Metabolic Syndrome.	Zhang Y et al.	—	2025	→
Integrated Bioinformatics Analysis and Experimental Validation of the Role of Cellular Senescence in Osteoporosis.	Wang P et al.	—	2025	→
Integrated bioinformatics and validation reveal TMEM45A in systemic lupus erythematosus regulating atrial fibrosis in atrial fibrillation.	Xu H et al.	—	2025	→
Integrated Computational and Functional Screening Identifies G9a Inhibitors for SETD2-mutant Leukemia.	Zhang Y et al.	—	2025	→
Integrated machine learning constructed a circadian-rhythm-related model to assess clinical outcomes and therapeutic advantages in hepatocellular carcinoma.	Xu Z et al.	—	2025	→
Integrating axis quantitative trait loci looks beyond cell types and offers insights into brain-related traits.	Wang L et al.	—	2025	→
Integrating Bulk RNA Sequencing and CRISPR-Cas9 Screening to Identify Proliferation-Related Genes for Prognostic Stratification in Breast Cancer.	Wang G et al.	—	2025	→
Integrating Genetic and Single-Cell Genomic Data to Reveal Brain Cell-Specific Regulation of Attention-Deficit/Hyperactivity Disorder Risk in the Prefrontal Cortex.	Gui J et al.	—	2025	→
Integrating imaging and omics for enhanced subtyping of mild cognitive impairment associated with Alzheimer's disease.	Afxenti S et al.	—	2025	→
Integrating Network Analysis and Machine Learning Identifies Key Autism Spectrum Disorder Genes Linked to Immune Dysregulation and Therapeutic Targets.	Wang H et al.	—	2025	→
Integrating pharmacogenomics and cheminformatics with diverse disease phenotypes for cell type-guided drug discovery.	Halu A et al.	—	2025	→
Integrating population-level and cell-based signatures for drug repositioning.	He C et al.	—	2025	→
Integration of multiple machine learning approaches develops a gene mutation-based classifier for accurate immunotherapy outcomes.	Shi R et al.	—	2025	→
Integration of Single Cell and Bulk RNA-Sequencing Reveals Key Genes and Immune Cell Infiltration to Construct a Predictive Model and Identify Drug Targets in Endometriosis.	Zhang H et al.	—	2025	→
Integrative analysis of lung adenocarcinoma across diverse ethnicities and exposures.	Satpathy S et al.	—	2025	→
Integrative analysis using machine learning and RNA sequencing identifies TGFBI as a therapeutic target in HIV-associated osteonecrosis of the femoral head.	Yuan W et al.	—	2025	→
Integrative bioinformatics and drug repurposing for metastatic prostate cancer: identifying novel therapeutic targets by transcriptional profiling and molecular Modeling.	Nisar H et al.	—	2025	→
Integrative genomic and bioinformatic prioritization of drug repurposing candidates for prostate cancer.	Irham LM et al.	—	2025	→
Integrative multi-omics and experimental analyses implicate PTK2 as a lorazepam-associated biomarker and potential therapeutic target in ovarian cancer.	Hong X et al.	—	2025	→
Integrative transcriptomic analysis identifies emetine as a promising candidate for overcoming acquired resistance to ALK inhibitors in lung cancer.	Park SM et al.	—	2025	→
Knowledge-Based Artificial Intelligence System for Drug Prioritization.	Su Y et al.	—	2025	→
L2S2: chemical perturbation and CRISPR KO LINCS L1000 signature search engine.	Marino GB et al.	—	2025	→
Large-scale dependency and drug screens to characterize the therapeutic vulnerabilities of multiple myeloma with 1q.	Sklavenitis-Pistofidis R et al.	—	2025	→
Leveraging pharmacovigilance data to predict population-scale toxicity profiles of checkpoint inhibitor immunotherapy.	Yan D et al.	—	2025	→
Leveraging pleiotropy for the improved treatment of psychiatric disorders.	Woodward DJ et al.	—	2025	→
Leveraging Transcriptional Readouts as a Platform for Drug Repurposing in Cardiomyopathy.	Mahmoud AI et al.	—	2025	→
Lung NR3C1<sup>+</sup> and CXCR6<sup>high</sup> T cells distinguish immunopathogenesis of human emphysema.	Zhang Y et al.	—	2025	→
Lung Single-Cell Transcriptomics Reveal Diverging Pathobiology and Opportunities for Precision Targeting in Scleroderma-Associated Versus Idiopathic Pulmonary Arterial Hypertension.	Tuhy T et al.	—	2025	→
Machine learning analysis of FOSL2 and RHoBTB1 as central immunological regulators in knee osteoarthritis synovium.	Gao K et al.	—	2025	→
Machine Learning Approaches for the Identification of Genetic Interactions.	Dey A et al.	—	2025	→
Machine learning combining external validation to explore the immunopathogenesis of diabetic foot ulcer and predict therapeutic drugs.	Lu Z et al.	—	2025	→
Machine learning to dissect perturbations in complex cellular systems.	Monfort-Lanzas P et al.	—	2025	→
macpie: Scalable workflow for high-throughput transcriptomic profiling.	Bartonicek N et al.	—	2025	→
Maternal exposure to polystyrene nanoplastics induces sex-specific kidney injury in offspring.	Chen X et al.	—	2025	→
MD-Syn: synergistic drug combination prediction based on a multidimensional feature fusion method and attention mechanisms.	Ge X et al.	—	2025	→
Mechanism and Efficacy of Etanercept in Treating Autoimmune-like Manifestations of Coronavirus Disease 2019 in elderly individuals.	Zhang L et al.	—	2025	→
Metabolic expression profiling analysis reveals pyruvate-mediated EPHB2 upregulation promotes lymphatic metastasis in head and neck squamous cell carcinomas.	Miao J et al.	—	2025	→
Metabolic mapping of the human solute carrier superfamily.	Wiedmer T et al.	—	2025	→
Metformin sensitizes triple-negative breast cancer to histone deacetylase inhibitors by targeting FGFR4.	Gu Z et al.	—	2025	→
Molecular Clustering of Metabolic Dysfunction-Associated Steatotic Liver Disease Based on Transcriptome Analysis.	Ryu G et al.	—	2025	→
Molecular Subtypes and Biomarkers of Ulcerative Colitis Revealed by Sphingolipid Metabolism-Related Genes: Insights from Machine Learning and Molecular Dynamics.	Li Q et al.	—	2025	→
MORF: Multi-view oblique random forest for hepatotoxicity prediction.	Sui B et al.	—	2025	→
Morphological map of under- and overexpression of genes in human cells.	Chandrasekaran SN et al.	—	2025	→
Multi-gradient permutation survival analysis identifies mitosis and immune signatures steadily associated with cancer patient prognosis.	Cai X et al.	—	2025	→
Multi-modal characterization of metabolic and immune gene clusters in adrenocortical carcinoma treatment.	Hao W et al.	—	2025	→
Multi-omic analyses reveal PTPN6's impact on tumor immunity across various cancers.	Zhong Y et al.	—	2025	→
Multiomics Analysis Reveals Neuroblastoma Molecular Signature Predicting Risk Stratification and Tumor Microenvironment Differences.	Zhou X et al.	—	2025	→
Multi-omics derivation of a core gene signature for predicting therapeutic response and characterizing immune dysregulation in inflammatory bowel disease.	Wang M et al.	—	2025	→
Multi-Omics Profiling Identifies a High-Risk Subgroup of Breast Cancer Stem Cells for Prognostic Stratification and Personalized Treatment.	Wang G et al.	—	2025	→
Multi-scale data reveal a CD24(+) MUCL1(+) tumor subgroup associated with unfavorable prognosis in ER+ breast cancer.	Li Y et al.	—	2025	→
Multi-view gene panel characterization for spatially resolved omics.	Kim D et al.	—	2025	→
Natural lignan justicidin A-induced mitophagy as a targetable niche in bladder cancer.	Chang KH et al.	—	2025	→
Network controllability analysis reveals the antiviral potential of Etravirine against hepatitis E virus infection.	Ansari S et al.	—	2025	→
Novel machine learning model for predicting cancer drugs' susceptibilities and discovering novel treatments.	Cao X et al.	—	2025	→
Olmesartan Restores <i>LMNA</i> Function in Haploinsufficient Cardiomyocytes.	Kort EJ et al.	—	2025	→
Overview and limitations of database in global traditional medicines: A narrative review.	Li XL et al.	—	2025	→
Pan-cancer analysis reveals age-associated genetic alterations in protein domains.	Zou H et al.	—	2025	→
Pathogenic Concepts in Pulmonary Arterial Hypertension Revisited: A Multigenerational Perspective.	Kwapiszewska G et al.	—	2025	→
Patient-centered brain transcriptomic and multimodal imaging determinants of clinical progression, physical activity, and treatment needs in Parkinson's disease.	Adewale Q et al.	—	2025	→
Pattern Recognition Algorithms in Pharmacogenomics and Drug Repurposing-Case Study: Ribavirin and Lopinavir.	Calvo H et al.	—	2025	→
PerturBase: a comprehensive database for single-cell perturbation data analysis and visualization.	Wei Z et al.	—	2025	→
PerturbDB for unraveling gene functions and regulatory networks.	Yang B et al.	—	2025	→
PerturbNet predicts single-cell responses to unseen chemical and genetic perturbations.	Yu H et al.	—	2025	→
PerturbSeq.db: An Integrated Repository for Comprehensive Analysis of Single-cell Perturbation Data.	He T et al.	—	2025	→
PhaSeDis: A Manually Curated Database of Phase Separation-disease Associations and Corresponding Small Molecules.	Chen T et al.	—	2025	→
Phenotypic complexities of rare heterozygous neurexin-1 deletions.	Fernando MB et al.	—	2025	→
Plasticity of Gene Expression in Spaceflight and Postflight in Relation to Cardiovascular Disease: Mechanisms and Candidate Repurposed Drugs.	Bourdakou MM et al.	—	2025	→
Playbook workflow builder: Interactive construction of bioinformatics workflows.	Clarke DJB et al.	—	2025	→
Potential role of hypobaric hypoxia environment in treating pan-cancer.	Zhang S et al.	—	2025	→
Precision cardiovascular medicine: shifting the innovation paradigm.	Aikawa M et al.	—	2025	→
Predicting in vitro assays related to liver function using probabilistic machine learning.	Morelli FM et al.	—	2025	→
Prediction of adverse drug reactions based on pharmacogenomics combination features: a preliminary study.	He M et al.	—	2025	→
Prediction of cellular morphology changes under perturbations with a transcriptome-guided diffusion model.	Wang X et al.	—	2025	→
Prediction of Drug-Induced Nephrotoxicity Using Chemical Information and Transcriptomics Data.	Chenga H et al.	—	2025	→
Prediction of protein subcellular localization in single cells.	Zhang X et al.	—	2025	→
Predictive gene expression signatures for Alzheimer's disease using post-mortem brain tissue.	Duche AH et al.	—	2025	→
Prioritizing repurposable drugs for Alzheimer's disease using network-based analysis with concurrent assessment of Long QT syndrome risk.	Funari A et al.	—	2025	→
Profiling Multiple CD8+ T-cell Functional Dimensions Enhances Breast Cancer Immune Assessment.	Liang Z et al.	—	2025	→
Prognostic impact of caspase-8 mutation in oral cavity squamous cell carcinoma.	Lu HJ et al.	—	2025	→
Progress in toxicogenomics to protect human health.	Meier MJ et al.	—	2025	→
Proinflammatory transcriptomic and kinomic alterations in astrocytes derived from patients with familial Alzheimer's disease.	Siciliano B et al.	—	2025	→
Protein-Protein Interactions in Papillary and Nonpapillary Urothelial Carcinoma Architectures: Comparative Study.	Chou C et al.	—	2025	→
Proteomic-based stemness score measures oncogenic dedifferentiation and enables the identification of druggable targets.	Kołodziejczak-Guglas I et al.	—	2025	→
Protocol to infer off-target effects of drugs on cellular signaling using interactome-based deep learning.	Meimetis N et al.	—	2025	→
Quantifying and interpreting biologically meaningful spatial signatures within tumor microenvironments.	Jing SY et al.	—	2025	→
RAB7B as a Potential Therapeutic Target in Liver Cirrhosis: Insights from Protein Expression and Bioinformatics Analyses.	Dai J et al.	—	2025	→
Rapid assay development for low input targeted proteomics using a versatile linear ion trap.	Shannon AE et al.	—	2025	→
Rationally Designed Functionalized Phytochemical-Conjugated Fullerene Quantum Dots Inhibiting Viral Chaperone Activity and RNA-Dependent RNA Polymerase in Nipah Virus.	Malarvizhi GL et al.	—	2025	→
Reconciling multiple connectivity-based systems biology methods for drug repurposing.	Gonzalez Gomez C et al.	—	2025	→
Reduced GATA3 expression associates with immuno-metabolic alterations and aggressive features in breast cancer.	Sæle AK et al.	—	2025	→
Reference-based chemical-genetic interaction profiling to elucidate small molecule mechanism of action in Mycobacterium tuberculosis.	Bond AN et al.	—	2025	→
Repositioning drugs for autism spectrum disorder: An integrated network analysis of blood and brain tissue key driver genes.	Zhang C et al.	—	2025	→
Repurposed doxepin targeting host AXL kinase to disrupt viral 2C-mediated immune evasion in Coxsackievirus B infection.	Yan R et al.	—	2025	→
Repurposing Amiodarone for Bladder Cancer Treatment.	Roa FJ et al.	—	2025	→
Repurposing methimazole to promote coronary collateral circulation through MAPK1-mediated macrophage polarization via ferroptosis.	Zhu LP et al.	—	2025	→
Repurposing of the Syk inhibitor fostamatinib using a machine learning algorithm.	Choi Y et al.	—	2025	→
Reversal gene expression assessment for drug repurposing, a case study of glioblastoma.	Sun S et al.	—	2025	→
REVIVE: a computational platform for systematically identifying rejuvenating chemical and genetic perturbations.	Jung S et al.	—	2025	→
RIDDEN: Data-driven inference of receptor activity from transcriptomic data.	Barsi S et al.	—	2025	→
Sappanone A, a potential natural inhibitor of PI3K, alleviates metabolic dysfunction-associated steatohepatitis in experimental models.	Qiao X et al.	—	2025	→
sc2DAT: workflow for targeting tumor subpopulations of single cells.	Marino GB et al.	—	2025	→
ScDrugAct: a comprehensive database to dissect tumor microenvironment cell heterogeneity contributing to drug action and resistance across human cancers.	Xu Y et al.	—	2025	→
Screening the Irish Marine Biorepository Identifies a New Bryostatin Analog as Potent Inhibitor of Activated B-Cells Diffuse Large B-Cell Lymphoma.	Jennings LK et al.	—	2025	→
Selective inhibition of stromal mechanosensing suppresses cardiac fibrosis.	Cho S et al.	—	2025	→
Sensitive detection of synthetic response to cancer immunotherapy driven by gene paralog pairs.	Dong C et al.	—	2025	→
Sepsis Important Genes Identification Through Biologically Informed Deep Learning and Transcriptomic Analysis.	Li R et al.	—	2025	→
Signature-based repurposed drugs resemble the inhibition of TGFβ-induced NDRG1 as potential therapeutics for triple-negative breast cancer.	López-Tejada A et al.	—	2025	→
SIMD: Synergistic integration mutualistic platform based on single-cell and proteotranscriptomics for drug repositioning.	Lee SY et al.	—	2025	→
Single-cell multi-omics analysis reveals cancer regulatory elements of transcriptional programs and clinical implications.	Tang X et al.	—	2025	→
Single-Cell Sequencing of Human Neural Organoids in a Model of Intracerebral Hemorrhage Reveals Temporally Dynamic Responses to Blood.	Seah C et al.	—	2025	→
Single-cell Technology in Stem Cell Research.	Golchin A et al.	—	2025	→
Single-Cell Transcriptional Profiling Reveals Cell Type-Specific Sex-Dependent Molecular Patterns of Schizophrenia.	Zhou R et al.	—	2025	→
Sirolimus as a repurposed drug for tendinopathy: A systems biology approach combining computational and experimental methods.	Wang Z et al.	—	2025	→
SOAR elucidates biological insights and empowers drug discovery through spatial transcriptomics.	Li Y et al.	—	2025	→
SPP1+ tumor-associated macrophages define a high-risk subgroup and inform personalized therapy in hepatocellular carcinoma.	Xu WX et al.	—	2025	→
SSL-VQ: vector-quantized variational autoencoders for semi-supervised prediction of therapeutic targets across diverse diseases.	Namba S et al.	—	2025	→
Stage-dependent proteomic alterations in aqueous humor of diabetic retinopathy patients based on data-independent acquisition and parallel reaction monitoring.	Jin Y et al.	—	2025	→
Strategies for <i>in Silico</i> Drug Discovery to Modulate Macromolecular Interactions Altered by Mutations.	Poudel P et al.	—	2025	→
Striatal cell-type-specific molecular signatures reveal potential therapeutic targets in a model of dystonia.	Roman KM et al.	—	2025	→
Structure-enhanced graph meta learning for few-shot gene regulatory network inference.	Yu W et al.	—	2025	→
SynergyGraph: predicting cell line specific drug combination synergy scores using knowledge graph representation and hypergraph modeling.	Mehrabani M et al.	—	2025	→
SynergyImage: image-based model for drug combinations synergy score prediction.	Mehrabani M et al.	—	2025	→
SynVerse: a modular framework for building and evaluating deep learning-based drug synergy prediction models.	Tasnina N et al.	—	2025	→
Systematic analysis of the transcriptional landscape of melanoma reveals drug-target expression plasticity.	Balderson B et al.	—	2025	→
Targeting TCMR-associated cytokine genes for drug screening identifies PPARγ agonists as novel immunomodulatory agents in transplantation.	Hu L et al.	—	2025	→
Targeting TYROBP to influence the immune microenvironment and osteogenic differentiation of mesenchymal stem cells.	Huang L et al.	—	2025	→
The cardiac glycoside periplocymarin sensitizes gastric cancer to ferroptosis via the ATP1A1-Src-YAP/TAZ-TFRC axis.	Ke A et al.	—	2025	→
The connection between Bayesian networks and adverse outcome pathway (AOP) networks and how to use it for predicting drug toxicity.	Wang D et al.	—	2025	→
The evolution of Alzheimer's target identification: Towards a fusion of artificial and cellular intelligence.	Wittenberg G et al.	—	2025	→
The evolving landscape of cancer cachexia prevention: A review of metronomic chemotherapy and drug repurposing strategies.	Thakur A et al.	—	2025	→
The future of metronomic chemotherapy: experimental and computational approaches of drug repurposing.	Abdelrady YA et al.	—	2025	→
The Hypomethylating Agent 5-Azacitidine Potentiates the Effect of RAS and Sp1 Inhibitors in Neuroblastoma Cells.	Ivanenko KA et al.	—	2025	→
The Marine Natural Compound Aplysinamisine I Selectively Induces Apoptosis and Exhibits Synergy with Taxol™ in Triple-Negative Breast Cancer Spheroids.	Guzmán EA et al.	—	2025	→
Therapeutic target prediction for orphan diseases integrating genome-wide and transcriptome-wide association studies.	Namba S et al.	—	2025	→
The Role of PLIN3 in Prognosis and Tumor-Associated Macrophage Infiltration: A Pan-Cancer Analysis.	Yang S et al.	—	2025	→
TIAM1 drives prostatic branching phenotype and is a potential therapeutic target for benign prostatic hyperplasia.	Khedmatgozar H et al.	—	2025	→
TOPK promotes immune suppression in kidney renal clear cell carcinoma and emerges as a prognostic and therapeutic target.	Zheng Z et al.	—	2025	→
Topoisomerase inhibitor amonafide enhances defense responses to promote longevity in C. elegans.	Hu IM et al.	—	2025	→
Towards an interpretable deep learning model of cancer.	Nilsson A et al.	—	2025	→
ToxAssay: a hierarchical model-driven tool for advanced toxicogenomics biomarker discovery.	Rana MM et al.	—	2025	→
Transcriptional response to combination antiretroviral therapy predicts side effects and novel targets.	Lachmann A et al.	—	2025	→
Transcription-Driven Repurposing of Cardiotonic Steroids for Lithium Treatment of Severe Depression.	Killick R et al.	—	2025	→
Transcriptome Complexity Disentangled: A Regulatory Molecules Approach.	Asiaee A et al.	—	2025	→
Transcriptome-conditioned molecule generation via gene interaction-aware fragment modeling with a GPT-based architecture.	Koo B et al.	—	2025	→
Transcriptome-Guided Drug Repurposing Identifies Homoharringtonine (HHT) as a Candidate for Radiation-Induced Pulmonary Fibrosis.	Farh ME et al.	—	2025	→
Transcriptome-wide analyses delineate the genetic architecture of expression variation in atopic dermatitis.	Antonatos C et al.	—	2025	→
Transcriptomic-Driven Drug Repurposing Reveals SP600125 as a Promising Drug Candidate for the Treatment of Glial-Mesenchymal Transition in Glioblastoma.	Odarenko KV et al.	—	2025	→
Transcriptomic imputation identifies tissue-specific genes associated with cervical myelopathy.	Seah C et al.	—	2025	→
Transcriptomic Profile of Isocitrate Dehydrogenase Mutant Type of Lower-Grade Glioma Reveals Molecular Changes for Prognosis.	Cho SB	—	2025	→
Transcriptomic signatures and network-based methods uncover new senescent cell anti-apoptotic pathways and senolytics.	Olascoaga S et al.	—	2025	→
Transcriptomics of autoimmune diseases identifies FGFR1 as a target for pancreatic β-cell protection.	Yi X et al.	—	2025	→
Transcripts with high distal heritability mediate genetic effects on complex metabolic traits.	Tyler AL et al.	—	2025	→
Transfer Learning and Permutation-Invariance Improving Predicting Genome-Wide, Cell-Specific and Directional Interventions Effects of Complex Systems.	Wang B et al.	—	2025	→
Tumor heterogeneity assessment using single-cell RNA sequencing (scRNA-seq): applications in lung cancer for diagnosis and treatment.	Bica C et al.	—	2025	→
Understanding the Comorbidities Among Psychiatric Disorders, Chronic Low Back Pain, and Spinal Degenerative Disease Using Observational and Genetically Informed Analyses.	Qiu D et al.	—	2025	→
Unlocking drug modes of action with multi-dimensional high-throughput metabolic profiling.	—	—	2025	→
Unraveling the Anticancer Potential of SSRIs in Prostate Cancer by Combining Computational Systems Biology and <i>In Vitro</i> Analyses.	Bardaweel SK et al.	—	2025	→
Unraveling the Effects of Epigallocatechin-3-gallate on Hepatocellular Carcinoma Cells: A Comparative Analysis of Monolayer vs Multicellular Tumor Spheroids.	Dos Reis Simpronio M et al.	—	2025	→
Unsupervised cell line embedding using pairwise drug response correlation.	Kim Y et al.	—	2025	→
Untangling the complex mechanisms associated with Alzheimer's disease in elderly patients using high-throughput RNA sequencing data and next-generation knowledge discovery methods: Focus on potential gene signatures and drugs for dementia.	Alkhatabi HA et al.	—	2025	→
Using Integrated Bioinformatics Analysis to Identify Saponin Formosanin C as a Ferroptosis Inducer in Colorectal Cancer with p53 and Oncogenic KRAS.	Chen HC et al.	—	2025	→
Utilization of precision medicine digital twins for drug discovery in Alzheimer's disease.	Ren Y et al.	—	2025	→
Utilizing TP53 hotspot mutations as effective predictors of gemcitabine treatment outcome in non-small-cell lung cancer.	Tseng YH et al.	—	2025	→
WebCMap: an R package for high-throughput connectivity analysis within the CMap framework.	Kang H et al.	—	2025	→
Zebularine showed anti-tumor efficacy in clear cell renal cell carcinoma.	Xu H et al.	—	2025	→
5-aminosalicylic acid suppresses osteoarthritis through the OSCAR-PPARγ axis.	Kim J et al.	—	2024	→
Accelerating drug discovery and repurposing by combining transcriptional signature connectivity with docking.	Thorman AW et al.	—	2024	→
A cellular reporter system to evaluate endogenous fetal hemoglobin induction and screen for therapeutic compounds.	Verheul TCJ et al.	—	2024	→
A Comprehensive Investigation of Active Learning Strategies for Conducting Anti-Cancer Drug Screening.	Vasanthakumari P et al.	—	2024	→
A computational framework to in silico screen for drug-induced hepatocellular toxicity.	Zhao Y et al.	—	2024	→
A cross-disease resource of living human microglia identifies disease-enriched subsets and tool compounds recapitulating microglial states.	Tuddenham JF et al.	—	2024	→
A Deep Neural Network for Predicting Synergistic Drug Combinations on Cancer.	Yan S et al.	—	2024	→
A gene-based score for the risk stratification of stage IA lung adenocarcinoma.	Xiong Y et al.	—	2024	→
A genome-scale deep learning model to predict gene expression changes of genetic perturbations from multiplex biological networks.	Zhan L et al.	—	2024	→
A high throughput cell stretch device for investigating mechanobiology <i>in vitro</i>.	Pratt SJP et al.	—	2024	→
AI-empowered perturbation proteomics for complex biological systems.	Qian L et al.	—	2024	→
Akt enhances the vulnerability of cancer cells to VCP/p97 inhibition-mediated paraptosis.	Lee DM et al.	—	2024	→
A method for predicting drugs that can boost the efficacy of immune checkpoint blockade.	Xia Y et al.	—	2024	→
A mini-review on perturbation modelling across single-cell omic modalities.	Gavriilidis GI et al.	—	2024	→
A multi-modal framework improves prediction of tissue-specific gene expression from a surrogate tissue.	Xu Y et al.	—	2024	→
A multiomic investigation of lung adenocarcinoma molecular subtypes.	Liang KH et al.	—	2024	→
A Multistep In Silico Approach Identifies Potential Glioblastoma Drug Candidates via Inclusive Molecular Targeting of Glioblastoma Stem Cells.	Dogra N et al.	—	2024	→
A network-based trans-omics approach for predicting synergistic drug combinations.	Iida M et al.	—	2024	→
An integrated framework for prognosis prediction and drug response modeling in colorectal liver metastasis drug discovery.	Zhou X et al.	—	2024	→
An interpretable artificial intelligence framework for designing synthetic lethality-based anti-cancer combination therapies.	Wang J et al.	—	2024	→
A novel combination treatment for fragile X syndrome predicted using computational methods.	Chadwick W et al.	—	2024	→
A Novel Pyrazole Exhibits Potent Anticancer Cytotoxicity via Apoptosis, Cell Cycle Arrest, and the Inhibition of Tubulin Polymerization in Triple-Negative Breast Cancer Cells.	Borrego EA et al.	—	2024	→
Apigenin Suppresses MED28-Mediated Cell Growth in Human Liver Cancer Cells.	Chou JC et al.	—	2024	→
Application of artificial intelligence and machine learning in drug repurposing.	Ghandikota SK et al.	—	2024	→
A proteomic landscape of pharmacologic perturbations for functional relevance.	Liu Z et al.	—	2024	→
Architecting the metabolic reprogramming survival risk framework in LUAD through single-cell landscape analysis: three-stage ensemble learning with genetic algorithm optimization.	Sun X et al.	—	2024	→
Artificial intelligence and cheminformatics tools: a contribution to the drug development and chemical science.	Saifi I et al.	—	2024	→
Artificial Intelligence and Machine Learning Models for Predicting Drug-Induced Kidney Injury in Small Molecules.	Rao M et al.	—	2024	→
Artificial intelligence-driven drug repositioning uncovers efavirenz as a modulator of α-synuclein propagation: Implications in Parkinson's disease.	Kim JB et al.	—	2024	→
A scalable platform for efficient CRISPR-Cas9 chemical-genetic screens of DNA damage-inducing compounds.	Lin K et al.	—	2024	→
A SRC-slug-TGFβ2 signaling axis drives poor outcomes in triple-negative breast cancers.	Angel CZ et al.	—	2024	→
A strategy to detect metabolic changes induced by exposure to chemicals from large sets of condition-specific metabolic models computed with enumeration techniques.	Fresnais L et al.	—	2024	→
ATP1A1/BCL2L1 predicts the response of myelomonocytic and monocytic acute myeloid leukemia to cardiac glycosides.	Cerella C et al.	—	2024	→
AutoTransOP: translating omics signatures without orthologue requirements using deep learning.	Meimetis N et al.	—	2024	→
A versatile attention-based neural network for chemical perturbation analysis and its potential to aid surgical treatment: an experimental study.	Fan Z et al.	—	2024	→
Beta<sub>2</sub>-Adrenergic Suppression of Neuroinflammation in Treatment of Parkinsonism, with Relevance for Neurodegenerative and Neoplastic Disorders.	Inchiosa MA	—	2024	→
BiMPADR: A Deep Learning Framework for Predicting Adverse Drug Reactions in New Drugs.	Li S et al.	—	2024	→
Bioinformatics analysis revealed underlying molecular mechanisms associated with asthma severity and identified GABAergic related pathway as a potential therapy for Th2-high endotype asthma.	Gong R et al.	—	2024	→
Bioinformatics-based drug repositioning and prediction of the main active ingredients and potential mechanisms of action for the efficacy of Dan-Lou tablet.	Zhang J et al.	—	2024	→
Bridging systems biology and tissue engineering: Unleashing the full potential of complex 3D <i>in vitro</i> tissue models of disease.	Cadavid JL et al.	—	2024	→
Building a translational cancer dependency map for The Cancer Genome Atlas.	Shi X et al.	—	2024	→
CD74 as a prognostic and M1 macrophage infiltration marker in a comprehensive pan-cancer analysis.	Li RQ et al.	—	2024	→
CDCM: a correlation-dependent connectivity map approach to rapidly screen drugs during outbreaks of infectious diseases.	Liao J et al.	—	2024	→
CDS-DB, an omnibus for patient-derived gene expression signatures induced by cancer treatment.	Liu Z et al.	—	2024	→
Celastrol Pyrazine Derivative Alleviates Silicosis Progression via Inducing ROS-Mediated Apoptosis in Activated Fibroblasts.	Bai Y et al.	—	2024	→
Central inhibition of HDAC6 re-sensitizes leptin signaling during obesity to induce profound weight loss.	Guan D et al.	—	2024	→
Characterization of stem cell landscape and assessing the stemness degree to aid clinical therapeutics in hematologic malignancies.	Feng YD et al.	—	2024	→
Characterizing diseases using genetic and clinical variables: A data analytics approach.	Gollapalli M et al.	—	2024	→
Chromatin Remodeling-Related PRDM1 Increases Stomach Cancer Proliferation and Is Counteracted by Bromodomain Inhibitor.	Hung YH et al.	—	2024	→
Clinical Relevance and Drug Modulation of PPAR Signaling Pathway in Triple-Negative Breast Cancer: A Comprehensive Analysis.	Zhang Y et al.	—	2024	→
COADREADx: A comprehensive algorithmic dissection of colorectal cancer unravels salient biomarkers and actionable insights into its discrete progression.	Palaniappan A et al.	—	2024	→
CODEX: COunterfactual Deep learning for the in silico EXploration of cancer cell line perturbations.	Schrod S et al.	—	2024	→
Comorbidity-Guided Text Mining and Omics Pipeline to Identify Candidate Genes and Drugs for Alzheimer's Disease.	Oviya IR et al.	—	2024	→
Comparative evaluation of feature reduction methods for drug response prediction.	Firoozbakht F et al.	—	2024	→
Comparison of multiple modalities for drug response prediction with learning curves using neural networks and XGBoost.	Branson N et al.	—	2024	→
Compound Activity Prediction with Dose-Dependent Transcriptomic Profiles and Deep Learning.	Godinez WJ et al.	—	2024	→
Comprehensive pan-cancer analysis of FUTs family as prognostic and immunity markers based on multi-omics data.	Jia Z et al.	—	2024	→
Computational and artificial intelligence-based approaches for drug metabolism and transport prediction.	Dudas B et al.	—	2024	→
Computational biology approaches for drug repurposing.	Waseem T et al.	—	2024	→
Computational drug repurposing for primary hyperparathyroidism.	Kubat Öktem E et al.	—	2024	→
Computational identification of natural senotherapeutic compounds that mimic dasatinib based on gene expression data.	Meiners F et al.	—	2024	→
Computational Modeling to Identify Drugs Targeting Metastatic Castration-Resistant Prostate Cancer Characterized by Heightened Glycolysis.	Su MC et al.	—	2024	→
Computational Strategies for Assessing Adverse Outcome Pathways: Hepatic Steatosis as a Case Study.	Ortega-Vallbona R et al.	—	2024	→
Computer-aided drug discovery strategies for novel therapeutics for prostate cancer leveraging next-generating sequencing data.	Zhang W et al.	—	2024	→
Connectivity mapping-based identification of pharmacological inhibitor targeting HDAC6 in aggressive pancreatic ductal adenocarcinoma.	Atri P et al.	—	2024	→
Cross-disorder and disease-specific pathways in dementia revealed by single-cell genomics.	Rexach JE et al.	—	2024	→
Current advances in comprehensive omics data mining for oncology and cancer research.	Jeong E et al.	—	2024	→
dbCRAF: a curated knowledgebase for regulation of radiation response in human cancer.	Liu J et al.	—	2024	→
Deep representation learning of chemical-induced transcriptional profile for phenotype-based drug discovery.	Tong X et al.	—	2024	→
DendroX: multi-level multi-cluster selection in dendrograms.	Feng F et al.	—	2024	→
Developing the biomarker panels and drugs by proteomic analysis for autoimmune uveitis and posterior scleritis.	Li X et al.	—	2024	→
Development of a prognostic model related to homologous recombination deficiency in glioma based on multiple machine learning.	Gong Z et al.	—	2024	→
Development of Drug-Induced Gene Expression Ranking Analysis (DIGERA) and Its Application to Virtual Screening for Poly (ADP-Ribose) Polymerase 1 Inhibitor.	Cho H et al.	—	2024	→
DGDRP: drug-specific gene selection for drug response prediction via re-ranking through propagating and learning biological network.	Pak M et al.	—	2024	→
Dictionary of immune responses to cytokines at single-cell resolution.	Cui A et al.	—	2024	→
DIRECTEUR: transcriptome-based prediction of small molecules that replace transcription factors for direct cell conversion.	Hamano M et al.	—	2024	→
Discovery of a novel inhibitor of macropinocytosis with antiviral activity.	Porebski B et al.	—	2024	→
Discovery of therapeutic targets in cancer using chromatin accessibility and transcriptomic data.	Forbes AN et al.	—	2024	→
Disentanglement of single-cell data with biolord.	Piran Z et al.	—	2024	→
Disulfidptosis: A Novel Prognostic Criterion and Potential Treatment Strategy for Diffuse Large B-Cell Lymphoma (DLBCL).	Wang Y et al.	—	2024	→
drexml: A command line tool and Python package for drug repurposing.	Esteban-Medina M et al.	—	2024	→
DRSPRING: Graph convolutional network (GCN)-Based drug synergy prediction utilizing drug-induced gene expression profile.	Han J et al.	—	2024	→
Drug-drug interactions prediction based on deep learning and knowledge graph: A review.	Luo H et al.	—	2024	→
DrugRepoBank: a comprehensive database and discovery platform for accelerating drug repositioning.	Huang Y et al.	—	2024	→
Drug Repositioning for Amyloid Transthyretin Amyloidosis by Interactome Network Corrected by Graph Neural Networks and Transcriptome Analysis.	He S et al.	—	2024	→
Drug repositioning for immunotherapy in breast cancer using single-cell analysis.	Mohammadi E et al.	—	2024	→
Drug Repositioning of Inflammatory Bowel Disease Based on Co-Target Gene Expression Signature of Glucocorticoid Receptor and TET2.	Zhao X et al.	—	2024	→
Drug Repositioning Using Computer-aided Drug Design (CADD).	Rawat S et al.	—	2024	→
DrugRepPT: a deep pretraining and fine-tuning framework for drug repositioning based on drug's expression perturbation and treatment effectiveness.	Fan S et al.	—	2024	→
Drug repurposing and personalized treatment strategies for bipolar disorder using transcriptomics: an exploratory study.	Ziani PR et al.	—	2024	→
Drug Repurposing for COVID-19 by Constructing a Comorbidity Network with Central Nervous System Disorders.	Qian J et al.	—	2024	→
Drug Repurposing for Effective Alzheimer's Disease Medicines: Existing Methods and Novel Pharmacoepidemiological Approaches.	Roberts JA et al.	—	2024	→
Drug repurposing for glomerular diseases: an underutilized resource.	Ng MSY et al.	—	2024	→
Drug repurposing screening and mechanism analysis based on human colorectal cancer organoids.	Mao Y et al.	—	2024	→
Drug Repurposing Using FDA Adverse Event Reporting System (FAERS) Database.	Morris R et al.	—	2024	→
DrugReSC: targeting disease-critical cell subpopulations with single-cell transcriptomic data for drug repurposing in cancer.	Liu C et al.	—	2024	→
Drug-target interaction prediction by integrating heterogeneous information with mutual attention network.	Zhang Y et al.	—	2024	→
Drug target prediction through deep learning functional representation of gene signatures.	Chen H et al.	—	2024	→
Effect of smoking cessation medications on intracranial aneurysm risk: A Mendelian randomization study.	Liang X et al.	—	2024	→
Efficacy of novel agents against cellular models of familial platelet disorder with myeloid malignancy (FPD-MM).	Mill CP et al.	—	2024	→
Elongin B promotes breast cancer progression by ubiquitinating tumor suppressor p14/ARF.	Sui XY et al.	—	2024	→
Emerging Roles of Spatial Transcriptomics in Liver Research.	Fujiwara N et al.	—	2024	→
Emerging Treatment Approaches for COVID-19 Infection: A Critical Review.	Bharadwaj A et al.	—	2024	→
Empowering biomedical discovery with AI agents.	Gao S et al.	—	2024	→
Establishing and Validating an Innovative Focal Adhesion-Linked Gene Signature for Enhanced Prognostic Assessment in Endometrial Cancer.	Yan C et al.	—	2024	→
Exploiting open source omics data to advance pancreas research.	Swaminathan G et al.	—	2024	→
Exploration of a miRNA-mRNA network shared between acute pancreatitis and Epstein-Barr virus infection by integrated bioinformatics analysis.	Wei X et al.	—	2024	→
Exploring cutting-edge strategies for drug repurposing in female cancers - An insight into the tools of the trade.	Satish KS et al.	—	2024	→
Exploring potential biomarkers and therapeutic targets in inflammatory bowel disease: insights from a mega-analysis approach.	Stemmer E et al.	—	2024	→
Exploring the effects of experimental parameters and data modeling approaches on in vitro transcriptomic point-of-departure estimates.	Harrill JA et al.	—	2024	→
Exploring the Molecular Mechanism of Comorbidity of Type 2 Diabetes Mellitus and Colorectal Cancer: Insights from Bulk Omics and Single-Cell Sequencing Validation.	Luo Y et al.	—	2024	→
Exploring the molecular mechanisms of asthma across multiple datasets.	Guo L et al.	—	2024	→
Exploring the pathogenesis, biomarkers, and potential drugs for type 2 diabetes mellitus and acute pancreatitis through a comprehensive bioinformatic analysis.	Zhong L et al.	—	2024	→
Exploring the Synergistic Effects of Erinacines on Microglial Regulation and Alzheimer's Pathology Under Metabolic Stress.	Bui VT et al.	—	2024	→
Finding new analgesics: Computational pharmacology faces drug discovery challenges.	Barakat A et al.	—	2024	→
Fluorescent Phenotyping of Blood Cells Using a Differential Sensing Strategy: Differentiating Physiological Aging Stages and Neuro-Degenerative Disease Drugs.	Hoon Lee J et al.	—	2024	→
From genetic associations to genes: methods, applications, and challenges.	Qi T et al.	—	2024	→
From mechanism to application: Decrypting light-regulated denitrifying microbiome through geometric deep learning.	Liao Y et al.	—	2024	→
GeneCompass: deciphering universal gene regulatory mechanisms with a knowledge-informed cross-species foundation model.	Yang X et al.	—	2024	→
Gene expression profiles of precursor cells identify compounds that reduce NRP1 surface expression in macrophages: Implication for drug repositioning for COVID-19.	Iwata A et al.	—	2024	→
Gene panel selection for targeted spatial transcriptomics.	Zhang Y et al.	—	2024	→
Genetically Regulated Gene Expression in the Brain Associated With Chronic Pain: Relationships With Clinical Traits and Potential for Drug Repurposing.	Johnston KJA et al.	—	2024	→
Genetic imputation of kidney transcriptome, proteome and multi-omics illuminates new blood pressure and hypertension targets.	Xu X et al.	—	2024	→
Genetic influences on circulating retinol and its relationship to human health.	Reay WR et al.	—	2024	→
GexMolGen: cross-modal generation of hit-like molecules via large language model encoding of gene expression signatures.	Cheng J et al.	—	2024	→
GINS2 regulates temozolomide chemosensitivity via the EGR1/ECT2 axis in gliomas.	He H et al.	—	2024	→
Glioblastoma Multiforme miRNA based Comprehensive Study to Validate Phytochemicals for Effective Treatment against Deadly Tumour through <i>In Silico</i> Evaluation.	Khan RB et al.	—	2024	→
Harnessing Drug Repurposing to Combat Breast Cancer by Targeting Altered Metabolism and Epithelial-to-Mesenchymal Transition Pathways.	Kandasamy T et al.	—	2024	→
HDAC1/2 inhibitor therapy improves multiple organ systems in aged mice.	Tammaro A et al.	—	2024	→
HE2Gene: image-to-RNA translation via multi-task learning for spatial transcriptomics data.	Chen X et al.	—	2024	→
Herb-CMap: a multimodal fusion framework for deciphering the mechanisms of action in traditional Chinese medicine using Suhuang antitussive capsule as a case study.	Wang Y et al.	—	2024	→
Heterogeneous network approaches to protein pathway prediction.	Nayar G et al.	—	2024	→
High-resolution transcriptomics analysis of CXCL13<sup>+</sup> EPSTI1<sup>+</sup> CDK1<sup>+</sup> cells with a specific focus on lung adenocarcinoma.	Zeng L et al.	—	2024	→
High-Throughput Transcriptomics Screen of ToxCast Chemicals in U-2 OS Cells.	Bundy JL et al.	—	2024	→
Hyaluronic acid stimulation of stem cells for cardiac repair: a cell-free strategy for myocardial infarct.	Jeong SY et al.	—	2024	→
Identification and evaluation of candidate COVID-19 critical genes and medicinal drugs related to plasma cells.	Liu Z et al.	—	2024	→
Identification and validation of glycolysis-related diagnostic signatures in diabetic nephropathy: a study based on integrative machine learning and single-cell sequence.	Wu X et al.	—	2024	→
Identification of a gene network driving the attenuated response to lipopolysaccharide of monocytes from hypertensive coronary artery disease patients.	Lu C et al.	—	2024	→
Identification of a histone deacetylase inhibitor as a therapeutic candidate for congenital central hypoventilation syndrome.	Africano C et al.	—	2024	→
Identification of an early survival prognostic gene signature for localized osteosarcoma patients.	Patel TD et al.	—	2024	→
Identification of basement membrane-related signatures for estimating prognosis, immune infiltration landscape and drug candidates in pancreatic adenocarcinoma.	Zhou F et al.	—	2024	→
Identification of Brain Cell Type-Specific Therapeutic Targets for Glioma From Genetics.	Gui J et al.	—	2024	→
Identification of diagnostic signature, molecular subtypes, and potential drugs in allergic rhinitis based on an inflammatory response gene set.	Dai J et al.	—	2024	→
Identification of drug responsive enhancers by predicting chromatin accessibility change from perturbed gene expression profiles.	Wang Y et al.	—	2024	→
Identification of immune-related endoplasmic reticulum stress genes in proliferative diabetic retinopathy using bioinformatics analysis.	Chen H et al.	—	2024	→
Identification of Key Immune and Cell Cycle Modules and Prognostic Genes for Glioma Patients through Transcriptome Analysis.	Guo K et al.	—	2024	→
Identification of Lung Adenocarcinoma Subtypes Based on MHC-II Gene Expression Profile and Immunological Analysis.	Gao Y et al.	—	2024	→
Identification of metastasis-related genes for predicting prostate cancer diagnosis, metastasis and immunotherapy drug candidates using machine learning approaches.	Wang Y et al.	—	2024	→
Identification of Mitophagy-Associated Genes for the Prediction of Metabolic Dysfunction-Associated Steatohepatitis Based on Interpretable Machine Learning Models.	Deng B et al.	—	2024	→
Identification of PANoptosis-related predictors for prognosis and tumor microenvironment by multiomics analysis in glioma.	Sun F et al.	—	2024	→
Identification of Potentially Repurposable Drugs for Lewy Body Dementia Using a Network-Based Approach.	Manoj M et al.	—	2024	→
Identification of prognostic stemness-related genes in kidney renal papillary cell carcinoma.	Liu Y et al.	—	2024	→
Identification of senescence related hub genes and potential therapeutic compounds for dilated cardiomyopathy via comprehensive transcriptome analysis.	Du C et al.	—	2024	→
Identification of the metabolic protein ATP5MF as a potential therapeutic target of TNBC.	Chen K et al.	—	2024	→
Identifying compound-protein interactions with knowledge graph embedding of perturbation transcriptomics.	Ni S et al.	—	2024	→
Identifying Hub Genes and Metabolic Pathways in Collagen VI-Related Dystrophies: A Roadmap to Therapeutic Intervention.	Ceyhan AB et al.	—	2024	→
iDOMO: identification of drug combinations via multi-set operations for treating diseases.	Zhou X et al.	—	2024	→
IGSF1: a biomarker for predicting prognosis, immunotherapy response, and drug candidates in COVID-19 combined hepatocellular carcinoma.	Guo Y et al.	—	2024	→
Immune dysfunction mediated by the competitive endogenous RNA network in fetal side placental tissue of polycystic ovary syndrome.	Xie N et al.	—	2024	→
Immune Gene Networks from Lung Cancer Patients Treated with Immune Checkpoint Inhibitors.	Kim KS et al.	—	2024	→
Improving compound-protein interaction prediction by focusing on intra-modality and inter-modality dynamics with a multimodal tensor fusion strategy.	Wang M et al.	—	2024	→
Improving iPSC Differentiation Using a Nanodot Platform.	Chiew MY et al.	—	2024	→
Inactivation of pentraxin 3 suppresses M2-like macrophage activity and immunosuppression in colon cancer.	Chen FW et al.	—	2024	→
Inference of drug off-target effects on cellular signaling using interactome-based deep learning.	Meimetis N et al.	—	2024	→
Inhibition of PI3K/AKT signaling pathway prevents blood-induced heterotopic ossification of the injured tendon.	Xuri Chen et al.	—	2024	→
Inhibition of Selenoprotein I promotes ferroptosis and reverses resistance to platinum chemotherapy by impairing Akt phosphorylation in ovarian cancer.	Li J et al.	—	2024	→
Innovative target mining stratagems to navigate drug repurposing endeavours.	Saravanan KS et al.	—	2024	→
Insights into Drug Cardiotoxicity from Biological and Chemical Data: The First Public Classifiers for FDA Drug-Induced Cardiotoxicity Rank.	Seal S et al.	—	2024	→
In-Silico Identification of Novel Pharmacological Synergisms: The Trabectedin Case.	Mannarino L et al.	—	2024	→
Integrated analysis reveals a novel 5-fluorouracil resistance-based prognostic signature with promising implications for predicting the efficacy of chemotherapy and immunotherapy in patients with colorectal cancer.	Hou Y et al.	—	2024	→
Integrated landscape of plasma metabolism and proteome of patients with post-traumatic deep vein thrombosis.	Zhang K et al.	—	2024	→
Integrated multi-omics with machine learning to uncover the intricacies of kidney disease.	Liu X et al.	—	2024	→
Integrated transcriptomics- and structure-based drug repositioning identifies drugs with proteasome inhibitor properties.	Larsson P et al.	—	2024	→
Integrating Bulk and Single-cell RNA-seq to Construct a Macrophage-related Prognostic Model for Prognostic Stratification in Triple-negative Breast Cancer.	Zhao H et al.	—	2024	→
Integrating computational and experimental chemical biology revealed variable anticancer activities of phosphodiesterase isoenzyme 5 inhibitors (PDE5i) in lung cancer.	Bardaweel SK et al.	—	2024	→
Integrating protein interaction and pathway crosstalk network reveals a promising therapeutic approach for psoriasis through apoptosis induction.	Farahani M et al.	—	2024	→
Integrating single-cell transcriptomics with cellular phenotypes: cell morphology, Ca<sup>2+</sup> imaging and electrophysiology.	Camunas-Soler J	—	2024	→
Integrating Transcriptomic and Structural Insights: Revealing Drug Repurposing Opportunities for Sporadic ALS.	Sunildutt N et al.	—	2024	→
Integration of 3D bioprinting and multi-algorithm machine learning identified glioma susceptibilities and microenvironment characteristics.	Tang M et al.	—	2024	→
Interactions between integrin α9β1 and VCAM-1 promote neutrophil hyperactivation and mediate poststroke DVT.	Pandey N et al.	—	2024	→
Investigating the Role of Inflammatory Response in Polycystic Ovary Syndrome Using Integrated RNA-Seq Analysis.	Liu L et al.	—	2024	→
Investigation of the General Molecular Mechanisms of Gallic Acid via Analyses of Its Transcriptome Profile.	Kim J et al.	—	2024	→
KORE-Map 1.0: Korean medicine Omics Resource Extension Map on transcriptome data of tonifying herbal medicine.	Park M et al.	—	2024	→
Lansoprazole Ameliorates Isoniazid-Induced Liver Injury.	Wakai E et al.	—	2024	→
Learning representations for image-based profiling of perturbations.	Moshkov N et al.	—	2024	→
Leveraging metabolic modeling and machine learning to uncover modulators of quiescence depth.	Eames A et al.	—	2024	→
Lung Adenocarcinoma Systems Biomarker and Drug Candidates Identified by Machine Learning, Gene Expression Data, and Integrative Bioinformatics Pipeline.	Soyer SM et al.	—	2024	→
Luteolin Protects Against 6-Hydoroxydopamine-Induced Cell Death via an Upregulation of HRD1 and SEL1L.	Nishiguchi H et al.	—	2024	→
Major Facilitator Superfamily Domain Containing 5 Inhibition Reduces Lipoprotein(a) Uptake and Calcification in Valvular Heart Disease.	Rogers MA et al.	—	2024	→
Mapping drug biology to disease genetics to discover drug impacts on the human phenome.	Habib M et al.	—	2024	→
Mapping the human brain proteome: opportunities, challenges, and clinical potential.	Cartas-Cejudo P et al.	—	2024	→
MDTR: a knowledge-guided interpretable representation for quantifying liver toxicity at transcriptomic level.	Sung I et al.	—	2024	→
Mechanism-free repurposing of drugs for C9orf72-related ALS/FTD using large-scale genomic data.	Saez-Atienzar S et al.	—	2024	→
Metformin Therapeutic Targets for Aortic Aneurysms: A Mendelian Randomization and Colocalization Study.	Liu J et al.	—	2024	→
Mitophagy related diagnostic biomarkers for coronary in-stent restenosis identified using machine learning and bioinformatics.	Shen M et al.	—	2024	→
Modeling craniopharyngioma for drug screening reveals a neuronal mechanism for tumor growth.	Li S et al.	—	2024	→
Modulator of TMB-associated immune infiltration (MOTIF) predicts immunotherapy response and guides combination therapy.	Qian ZY et al.	—	2024	→
Molecular and functional landscape of malignant serous effusions for precision oncology.	Wegmann R et al.	—	2024	→
Molecular cascades and cell type-specific signatures in ASD revealed by single-cell genomics.	Wamsley B et al.	—	2024	→
Multi-Omics Analysis Identified Drug Repurposing Targets for Chronic Obstructive Pulmonary Disease.	Wang F et al.	—	2024	→
Multi-omics profiling of DNA methylation and gene expression alterations in human cocaine use disorder.	Zillich E et al.	—	2024	→
Multiplex single-cell chemical genomics reveals the kinase dependence of the response to targeted therapy.	McFaline-Figueroa JL et al.	—	2024	→
Multi role ChatGPT framework for transforming medical data analysis.	Chen H et al.	—	2024	→
Multi-tissue transcriptome-wide association study reveals susceptibility genes and drug targets for insulin resistance-relevant phenotypes.	Duan YY et al.	—	2024	→
NaCTR: Natural product-derived compound-based drug discovery pipeline from traditional oriental medicine by search space reduction.	Jung S et al.	—	2024	→
Navigating the complexities of drug development for inflammatory bowel disease.	Honap S et al.	—	2024	→
Neoadjuvant gemcitabine-cisplatin plus tislelizumab in persons with resectable muscle-invasive bladder cancer: a multicenter, single-arm, phase 2 trial.	Li K et al.	—	2024	→
Network-based cytokine inference implicates Oncostatin M as a driver of an inflammation phenotype in knee osteoarthritis.	Iijima H et al.	—	2024	→
Network-based screening identifies sitagliptin as an antitumor drug targeting dendritic cells.	Ng II et al.	—	2024	→
Network medicine analysis for dissecting the therapeutic mechanism of consensus TCM formulae in treating hepatocellular carcinoma with different TCM syndromes.	Gao K et al.	—	2024	→
Network pharmacology: an efficient but underutilized approach in oral, head and neck cancer therapy-a review.	Muthuramalingam P et al.	—	2024	→
Neurodegenerative pathways and metabolic changes in the hippocampus and cortex of mice exposed to urban particulate matter: Insights from an integrated interactome analysis.	Kim BY et al.	—	2024	→
New directions for Alzheimer's disease research from the Jackson Laboratory Center for Alzheimer's and Dementia Research 2022 workshop.	Telpoukhovskaia MA et al.	—	2024	→
Next-generation precision medicine for suicidality prevention.	Bhagar R et al.	—	2024	→
Novel insight into the etiology of ischemic stroke gained by integrative multiome-wide association study.	Jung J et al.	—	2024	→
Novel prognostic signature for hepatocellular carcinoma using a comprehensive machine learning framework to predict prognosis and guide treatment.	Zheng S et al.	—	2024	→
NP-TCMtarget: a network pharmacology platform for exploring mechanisms of action of traditional Chinese medicine.	Wang A et al.	—	2024	→
Nucleolar stress caused by arginine-rich peptides triggers a ribosomopathy and accelerates aging in mice.	Sirozh O et al.	—	2024	→
Opportunities for use of neuroimaging in de-risking drug development and improving clinical outcomes in psychiatry: an industry perspective.	Etkin A et al.	—	2024	→
Optimizing in silico drug discovery: simulation of connected differential expression signatures and applications to benchmarking.	Gonzalez Gomez C et al.	—	2024	→
Orthogonal proteogenomic analysis identifies the druggable PA2G4-MYC axis in 3q26 AML.	Marchesini M et al.	—	2024	→
Overcoming Therapy Resistance in Colorectal Cancer: Targeting the Rac1 Signaling Pathway as a Potential Therapeutic Approach.	Anselmino LE et al.	—	2024	→
Oxyresveratrol as a novel ferroptosis inducer exhibits anticancer activity against breast cancer via the EGFR/PI3K/AKT/GPX4 signalling axis.	Xiang L et al.	—	2024	→
Pan-cancer proteogenomics characterization of tumor immunity.	Petralia F et al.	—	2024	→
Partial correlation network analysis identifies coordinated gene expression within a regional cluster of COPD genome-wide association signals.	Gentili M et al.	—	2024	→
PCLAF-DREAM drives alveolar cell plasticity for lung regeneration.	Kim B et al.	—	2024	→
Penfluridol suppresses MYC-driven ANLN expression and liver cancer progression by disrupting the KEAP1-NRF2 interaction.	Nguyen MT et al.	—	2024	→
Perturbation-specific transcriptional mapping for unbiased target elucidation of antibiotics.	Romano KP et al.	—	2024	→
Petagraph: A large-scale unifying knowledge graph framework for integrating biomolecular and biomedical data.	Stear BJ et al.	—	2024	→
PharmGWAS: a GWAS-based knowledgebase for drug repurposing.	Kang H et al.	—	2024	→
Polypharmacology prediction: the long road toward comprehensively anticipating small-molecule selectivity to de-risk drug discovery.	Manen-Freixa L et al.	—	2024	→
Population-based high-dimensional analyses identify multiple intrinsic characters for cancer vaccines against lung squamous cell carcinoma.	Zeng L et al.	—	2024	→
PP2A complex disruptor SET prompts widespread hypertranscription of growth-essential genes in the pancreatic cancer cells.	Xu H et al.	—	2024	→
Precision oncology in neurofibromatosis type 1: quantification of differential sensitivity to selumetinib in plexiform neurofibromas using single-cell RNA sequencing.	Bhandarkar AR et al.	—	2024	→
Predicting single-cell cellular responses to perturbations using cycle consistency learning.	Huang W et al.	—	2024	→
Predicting transcriptional changes induced by molecules with MiTCP.	Yang K et al.	—	2024	→
Predicting transcriptional responses to novel chemical perturbations using deep generative model for drug discovery.	Qi X et al.	—	2024	→
Prediction of Endocrine-Disrupting Chemicals Related to Estrogen, Androgen, and Thyroid Hormone (EAT) Modalities Using Transcriptomics Data and Machine Learning.	Ollitrault G et al.	—	2024	→
Prediction of prognostic and immune therapy response in lung adenocarcinoma based on MHC-I-related genes.	Xu H et al.	—	2024	→
Predictive biomarkers for response to TGF- β inhibition in resensitizing chemo(radiated) esophageal adenocarcinoma.	Liu D et al.	—	2024	→
Prioritizing susceptibility genes for the prognosis of male-pattern baldness with transcriptome-wide association study.	Choi E et al.	—	2024	→
PRKCSH serves as a potential immunological and prognostic biomarker in pan-cancer.	Wang Q et al.	—	2024	→
Profibrotic Subsets of SPP1<sup>+</sup> Macrophages and POSTN<sup>+</sup> Fibroblasts Contribute to Fibrotic Scarring in Acne Keloidalis.	Hong YK et al.	—	2024	→
Prognostic value and therapeutic potential of NEK family in stomach adenocarcinoma.	Zhou X et al.	—	2024	→
Protective effect and mechanism of Qingfei Paidu decoction on myocardial damage mediated by influenza viruses.	Du L et al.	—	2024	→
Proteomic analysis of the urothelial cancer landscape.	Dressler FF et al.	—	2024	→
Proteomic basis for pancreatic acinar cell carcinoma and pancreatoblastoma as similar yet distinct entities.	Tanaka A et al.	—	2024	→
Proteomics Meets Dose Response: A New Paradigm for Deciphering Drug Effects.	Wang C et al.	—	2024	→
Proteomics Sequencing Reveals the Role of TGF-β Signaling Pathway in the Peripheral Blood of Offspring Rats Exposed to Fluoride.	Yu FF et al.	—	2024	→
PSME2 offers value as a biomarker of M1 macrophage infiltration in pan-cancer and inhibits osteosarcoma malignant phenotypes.	Li R et al.	—	2024	→
Psychosocial moderators of polygenic risk scores of inflammatory biomarkers in relation to GrimAge.	Tamman AJF et al.	—	2024	→
Pulmonary Effects of Traumatic Brain Injury in Mice: A Gene Set Enrichment Analysis.	Chan WH et al.	—	2024	→
Radiomic profiles improve prognostication and reveal targets for therapy in cervical cancer.	Halle MK et al.	—	2024	→
Recent Advances in and Application of Fluorescent Microspheres for Multiple Nucleic Acid Detection.	Chen Z et al.	—	2024	→
ReCorDE: a framework for identifying drug classes targeting shared vulnerabilities with applications to synergistic drug discovery.	John AJ et al.	—	2024	→
Reinventing gene expression connectivity through regulatory and spatial structural empowerment via principal node aggregation graph neural network.	Yan F et al.	—	2024	→
Repositioning the existing drugs for neuroinflammation: a fusion of computational approach and biological validation to counter the Parkinson's disease progression.	Tiwari H et al.	—	2024	→
Repositioning VU-0365114 as a novel microtubule-destabilizing agent for treating cancer and overcoming drug resistance.	Hsieh YY et al.	—	2024	→
Repurposed AT9283 triggers anti-tumoral effects by targeting MKK3 oncogenic functions in Colorectal Cancer.	Piastra V et al.	—	2024	→
RNA sequencing identifies lung cancer lineage and facilitates drug repositioning.	Zeng L et al.	—	2024	→
RNA Sequencing in Disease Diagnosis.	Smail C et al.	—	2024	→
Rummagene: massive mining of gene sets from supporting materials of biomedical research publications.	Clarke DJB et al.	—	2024	→
Ruxolitinib Improves Immune-Dysregulation Features but not Epigenetic Abnormality in a Patient with STAT1 GOF.	Koh JY et al.	—	2024	→
sc2MeNetDrug: A computational tool to uncover inter-cell signaling targets and identify relevant drugs based on single cell RNA-seq data.	Feng J et al.	—	2024	→
SCAN: Spatiotemporal Cloud Atlas for Neural cells.	Deng Y et al.	—	2024	→
Senescence-associated microvascular endothelial dysfunction: A focus on the blood-brain and blood-retinal barriers.	Kim SY et al.	—	2024	→
Signature analysis of high-throughput transcriptomics screening data for mechanistic inference and chemical grouping.	Harrill JA et al.	—	2024	→
Signature reversion of three disease-associated gene signatures prioritizes cancer drug repurposing candidates.	Fisher JL et al.	—	2024	→
Signature Search Polestar: a comprehensive drug repurposing method evaluation assistant for customized oncogenic signature.	Zhang J et al.	—	2024	→
Single-cell genomics and regulatory networks for 388 human brains.	Emani PS et al.	—	2024	→
Single-cell transcriptomes identify patient-tailored therapies for selective co-inhibition of cancer clones.	Ianevski A et al.	—	2024	→
Single-cell transcriptomic profiling reveals a pathogenic role of cytotoxic CD4<sup>+</sup> T cells in giant cell arteritis.	Carmona EG et al.	—	2024	→
Single-nucleus sequencing reveals enriched expression of genetic risk factors in extratelencephalic neurons sensitive to degeneration in ALS.	Limone F et al.	—	2024	→
Standigm ASK™: knowledge graph and artificial intelligence platform applied to target discovery in idiopathic pulmonary fibrosis.	Han S et al.	—	2024	→
SuperFeat: Quantitative Feature Learning from Single-cell RNA-seq Data Facilitates Drug Repurposing.	Zhong J et al.	—	2024	→
SynergyX: a multi-modality mutual attention network for interpretable drug synergy prediction.	Guo Y et al.	—	2024	→
Systematic computational strategies for identifying protein targets and lead discovery.	Kataria A et al.	—	2024	→
Systematic investigation of chemo-immunotherapy synergism to shift anti-PD-1 resistance in cancer.	Wang Y et al.	—	2024	→
Systematic omics analysis identifies CCR6 as a therapeutic target to overcome cancer resistance to EGFR inhibitors.	Kwon EJ et al.	—	2024	→
Systems Biology Methods via Genome-Wide RNA Sequences to Investigate Pathogenic Mechanisms for Identifying Biomarkers and Constructing a DNN-Based Drug-Target Interaction Model to Predict Potential Molecular Drugs for Treating Atopic Dermatitis.	Chou SP et al.	—	2024	→
Tackling neurodegeneration <i>in vitro</i> with omics: a path towards new targets and drugs.	Carraro C et al.	—	2024	→
Targeting treatment resistance: unveiling the potential of RNA methylation regulators and TG-101,209 in pan-cancer neoadjuvant therapy.	Zhou Y et al.	—	2024	→
Text-mining-based feature selection for anticancer drug response prediction.	Wu G et al.	—	2024	→
The anti-leprosy drug clofazimine reduces polyQ toxicity through activation of PPARγ.	Li X et al.	—	2024	→
The broken Alzheimer's disease genome.	Gouveia Roque C et al.	—	2024	→
The Construction of a Multi-Gene Risk Model for Colon Cancer Prognosis and Drug Treatments Prediction.	Gao L et al.	—	2024	→
The efficacy of chemotherapy is limited by intratumoral senescent cells expressing PD-L2.	Chaib S et al.	—	2024	→
The Genomic Intersection of Oligodendrocyte Dynamics in Schizophrenia and Aging Unravels Novel Pathological Mechanisms and Therapeutic Potentials.	Rivera AD et al.	—	2024	→
The Molecular Circadian Clock Is a Target of Anti-cancer Translation Inhibitors.	Berthier A et al.	—	2024	→
The MT1 receptor as the target of ramelteon neuroprotection in ischemic stroke.	Zhang X et al.	—	2024	→
Tirzepatide's role in targeting adipose tissue macrophages to reduce obesity-related inflammation and improve insulin resistance.	Xia Y et al.	—	2024	→
Tracing back primed resistance in cancer via sister cells.	Dai J et al.	—	2024	→
Transcriptionally Conditional Recurrent Neural Network for De Novo Drug Design.	Matsukiyo Y et al.	—	2024	→
Transcriptomic Analyses Predict Enhanced Metabolic Activity and Therapeutic Potential of mTOR Inhibitors in Acne-Prone Skin.	Sennett ML et al.	—	2024	→
Transcriptomic analysis reveals <i>Streptococcus agalactiae</i> activation of oncogenic pathways in cervical adenocarcinoma.	Nguyen HDT et al.	—	2024	→
Transcriptomic insights into UTUC: role of inflammatory fibrosis and potential for personalized treatment.	Li K et al.	—	2024	→
Transcriptomics analysis reveals distinct mechanism of breast cancer stem cells regulation in mammospheres from MCF-7 and T47D cells.	Hermawan A et al.	—	2024	→
Transcriptomics-informed pharmacology identifies epigenetic and cell cycle regulators that enhance AAV production.	Tworig J et al.	—	2024	→
Transfer learning of condition-specific perturbation in gene interactions improves drug response prediction.	Bang D et al.	—	2024	→
TransGEM: a molecule generation model based on Transformer with gene expression data.	Liu Y et al.	—	2024	→
Triptolide and its prodrug Minnelide target high-risk MYC-amplified medulloblastoma in preclinical models.	Rodriguez-Blanco J et al.	—	2024	→
Tryptophan Metabolism in Alzheimer's Disease with the Involvement of Microglia and Astrocyte Crosstalk and Gut-Brain Axis.	Xie L et al.	—	2024	→
TTD: Therapeutic Target Database describing target druggability information.	Zhou Y et al.	—	2024	→
Tumor Organoids: The Era of Personalized Medicine.	Rassomakhina NV et al.	—	2024	→
Tumour evolution and microenvironment interactions in 2D and 3D space.	Mo CK et al.	—	2024	→
Unbiased discovery of cancer pathways and therapeutics using Pathway Ensemble Tool and Benchmark.	Wang L et al.	—	2024	→
Unraveling the complex relationship between mRNA and protein abundances: a machine learning-based approach for imputing protein levels from RNA-seq data.	Prabahar A et al.	—	2024	→
Unraveling transcriptomic signatures and dysregulated pathways in systemic lupus erythematosus across disease states.	Wang FQ et al.	—	2024	→
Unveiling hidden connections in omics data via pyPARAGON: an integrative hybrid approach for disease network construction.	Arici MK et al.	—	2024	→
Unveiling the hidden role of disulfidptosis in kidney renal clear cell carcinoma: a prognostic signature for personalized treatment.	Ye Y et al.	—	2024	→
Unveiling the Intricacies of Monoamine Oxidase-A (MAO-A) Inhibition in Colorectal Cancer: Computational Systems Biology, Expression Patterns, and the Anticancer Therapeutic Potential.	Bardaweel SK et al.	—	2024	→
Using network pharmacology to discover potential drugs for hypertrophic scars.	Zhang Y et al.	—	2024	→
voyAGEr, a free web interface for the analysis of age-related gene expression alterations in human tissues.	Schneider AL et al.	—	2024	→
Wnt-5a-Receptor Tyrosine Kinase-Like Orphan Receptor 2 Signaling Provokes Metastatic Colonization and Angiogenesis in Renal Cell Carcinoma, and Prunetin Supresses the Axis Activation.	Chuang WY et al.	—	2024	→
Wnt dose escalation during the exit from pluripotency identifies tranilast as a regulator of cardiac mesoderm.	Wu Z et al.	—	2024	→
Accumulation of α-synuclein mediates podocyte injury in Fabry nephropathy.	Braun F et al.	—	2023	→
A gene expression profile-based approach to screen the occurrence and predisposed host characteristics of drug-induced liver injury: a case study of <i>Psoralea corylifolia</i> Linn.	Zhang ML et al.	—	2023	→
A multi-omics analysis reveals CLSPN is associated with prognosis, immune microenvironment and drug resistance in cancers.	Chen Y et al.	—	2023	→
An association between ATP7B expression and human cancer prognosis and immunotherapy: a pan-cancer perspective.	Zhang Z et al.	—	2023	→
An integrated computational strategy to predict personalized cancer drug combinations by reversing drug resistance signatures.	Wang X et al.	—	2023	→
A novel signature incorporating lipid metabolism- and immune-related genes to predict the prognosis and immune landscape in hepatocellular carcinoma.	Yang T et al.	—	2023	→
An overview of recent advances and challenges in predicting compound-protein interaction (CPI).	Li Y et al.	—	2023	→
Antiepileptic drugs are endocrine disruptors for the human fetal testis ex vivo.	Lesné L et al.	—	2023	→
Applying a Gene Reversal Rate Computational Methodology to Identify Drugs for a Rare Cancer: Inflammatory Breast Cancer.	Ji X et al.	—	2023	→
Assessment of Drug-Induced Liver Injury through Cell Morphology and Gene Expression Analysis.	Lejal V et al.	—	2023	→
Ayurgenomics-based frameworks in precision and integrative medicine: Translational opportunities.	Mukerji M	—	2023	→
CAMK2D serves as a molecular scaffold for RNF8-MAD2 complex to induce mitotic checkpoint in glioma.	Chuah YH et al.	—	2023	→
Causal inference in drug discovery and development.	Michoel T et al.	—	2023	→
CDK4/6-MEK Inhibition in MPNSTs Causes Plasma Cell Infiltration, Sensitization to PD-L1 Blockade, and Tumor Regression.	Kohlmeyer JL et al.	—	2023	→
CDK6 is a novel predictive and prognosis biomarker correlated with immune infiltrates in multiple human neoplasms, including small cell lung carcinoma.	Li GS et al.	—	2023	→
Celastrol as a candidate drug for silicosis: From bioinformatics and network pharmacology to experimental validation.	Liang C et al.	—	2023	→
Chemical reprogramming for cell fate manipulation: Methods, applications, and perspectives.	Wang J et al.	—	2023	→
Chloroquine enhances the efficacy of chemotherapy drugs against acute myeloid leukemia by inactivating the autophagy pathway.	Wang HL et al.	—	2023	→
Clinical significance and potential application of cuproptosis-related genes in gastric cancer.	Yan JN et al.	—	2023	→
COIMMR: a computational framework to reveal the contribution of herbal ingredients against human cancer via immune microenvironment and metabolic reprogramming.	Tian S et al.	—	2023	→
COMO: a pipeline for multi-omics data integration in metabolic modeling and drug discovery.	Bessell B et al.	—	2023	→
Comprehensive analysis of miRNA-mRNA regulatory pairs associated with colorectal cancer and the role in tumor immunity.	Liu C et al.	—	2023	→
Comprehensive analysis of the prognosis and immune infiltration of TMC family members in renal clear cell carcinoma.	Tang W et al.	—	2023	→
Comprehensive profiling of extracellular vesicles in uveitis and scleritis enables biomarker discovery and mechanism exploration.	Wu L et al.	—	2023	→
COVID-19db linkage maps of cell surface proteins and transcription factors in immune cells.	Ramjattun K et al.	—	2023	→
D2H2: diabetes data and hypothesis hub.	Marino GB et al.	—	2023	→
Deep learning integrates histopathology and proteogenomics at a pan-cancer level.	Wang JM et al.	—	2023	→
Deep Learning-Predicted Dihydroartemisinin Rescues Osteoporosis by Maintaining Mesenchymal Stem Cell Stemness through Activating Histone 3 Lys 9 Acetylation.	Wang R et al.	—	2023	→
De Novo Design of Molecules with Multiaction Potential from Differential Gene Expression using Variational Autoencoder.	Pravalphruekul N et al.	—	2023	→
De novo drug design based on patient gene expression profiles via deep learning.	Yamanaka C et al.	—	2023	→
DepLink: an R Shiny app to systematically link genetic and pharmacologic dependencies of cancer.	Nayak T et al.	—	2023	→
Development and validation of a copper-related gene prognostic signature in hepatocellular carcinoma.	Shi H et al.	—	2023	→
Development of a MEK inhibitor, NFX-179, as a chemoprevention agent for squamous cell carcinoma.	Sarin KY et al.	—	2023	→
Dex-Benchmark: datasets and code to evaluate algorithms for transcriptomics data analysis.	Xie Z et al.	—	2023	→
Discovering Venom-Derived Drug Candidates Using Differential Gene Expression.	Romano JD et al.	—	2023	→
Distinct longevity mechanisms across and within species and their association with aging.	Tyshkovskiy A et al.	—	2023	→
DOSE-L1000: unveiling the intricate landscape of compound-induced transcriptional changes.	Wang J et al.	—	2023	→
DREAM: an R package for druggability evaluation of human complex diseases.	Federico A et al.	—	2023	→
Drug repurposing based on the similarity gene expression signatures to explore for potential indications of quercetin: a case study of multiple sclerosis.	Chen Y et al.	—	2023	→
Drug repurposing on Alzheimer's disease through modulation of NRF2 neighborhood.	Bourdakou MM et al.	—	2023	→
Drug Target Identification and Drug Repurposing in Psoriasis through Systems Biology Approach, DNN-Based DTI Model and Genome-Wide Microarray Data.	Zhan YP et al.	—	2023	→
EDST: a decision stump based ensemble algorithm for synergistic drug combination prediction.	Chen J et al.	—	2023	→
Elucidating disease-associated mechanisms triggered by pollutants via the epigenetic landscape using large-scale ChIP-Seq data.	Zou Z et al.	—	2023	→
Evaluation of the Involvement of Heme Oxygenase-1 Expression in Discoid Lupus Erythematosus Lesions.	Fagone P et al.	—	2023	→
Exploration of Artemisinin Against IgA Nephropathy via AKT/Nrf2 Pathway by Bioinformatics and Experimental Validation.	Yang WG et al.	—	2023	→
Exploration of prognosis and immunometabolism landscapes in ER+ breast cancer based on a novel lipid metabolism-related signature.	Shen L et al.	—	2023	→
Exploring DrugCentral: from molecular structures to clinical effects.	Halip L et al.	—	2023	→
Exploring the molecular mechanism of comorbidity of autism spectrum disorder and inflammatory bowel disease by combining multiple data sets.	Zhu J et al.	—	2023	→
Expression-Based Diagnosis, Treatment Selection, and Drug Development for Breast Cancer.	Ye Q et al.	—	2023	→
Few-Shot Drug Synergy Prediction With a Prior-Guided Hypernetwork Architecture.	Zhang QQ et al.	—	2023	→
FooDrugs: a comprehensive food-drug interactions database with text documents and transcriptional data.	Lacruz-Pleguezuelos B et al.	—	2023	→
FOXM1, MEK, and CDK4/6: New Targets for Malignant Peripheral Nerve Sheath Tumor Therapy.	Voigt E et al.	—	2023	→
Gene expression profiling in white blood cells reveals new insights into the molecular mechanisms of thalidomide in children with inflammatory bowel disease.	Pugnetti L et al.	—	2023	→
GeneRanger and TargetRanger: processed gene and protein expression levels across cells and tissues for target discovery.	Marino GB et al.	—	2023	→
Genetic and Epigenetic Host-Virus Network to Investigate Pathogenesis and Identify Biomarkers for Drug Repurposing of Human Respiratory Syncytial Virus via Real-World Two-Side RNA-Seq Data: Systems Biology and Deep-Learning Approach.	Hsu BW et al.	—	2023	→
Germline mechanisms of immunotherapy toxicities in the era of genome-wide association studies.	Gusev A	—	2023	→
Hypoxia induced responses are reflected in the stromal proteome of breast cancer.	Kjølle S et al.	—	2023	→
Identification of a novel 5-methylcytosine-related signature for prognostic prediction of kidney renal papillary cell carcinoma and a Putative target for drug repurposing.	Zhang Z et al.	—	2023	→
Identification of a novel competing endogenous RNA network and candidate drugs associated with ferroptosis in aldosterone-producing adenomas.	Hanxiao Y et al.	—	2023	→
Identification of drug candidates targeting monocyte reprogramming in people living with HIV.	Knoll R et al.	—	2023	→
Identification of drug repurposing candidates for the treatment of anxiety: A genetic approach.	Woodward DJ et al.	—	2023	→
Identification of endoplasmic reticulum stress-related biomarkers of diabetes nephropathy based on bioinformatics and machine learning.	Su J et al.	—	2023	→
Identification of immune-related genes in diagnosing retinopathy of prematurity with sepsis through bioinformatics analysis and machine learning.	Chen H et al.	—	2023	→
Identification of lncRNAs associated with T cells as potential biomarkers and therapeutic targets in lung adenocarcinoma.	Sun LU et al.	—	2023	→
Identification of novel anti-ZIKV drugs from viral-infection temporal gene expression profiles.	Zhang N et al.	—	2023	→
Identification of the enhancer RNAs related to tumorgenesis of pituitary neuroendocrine tumors.	Wang L et al.	—	2023	→
Identifying circRNA-associated-ceRNA networks in juvenile spondyloarthropathies patients.	Qijiao W et al.	—	2023	→
Identifying prognostic genes related PANoptosis in lung adenocarcinoma and developing prediction model based on bioinformatics analysis.	Zhang C et al.	—	2023	→
Identifying shared transcriptional risk patterns between atherosclerosis and cancer.	Baylis RA et al.	—	2023	→
Informatics on Drug Repurposing for Breast Cancer.	Zhou H et al.	—	2023	→
Inhibition of a lower potency target drives the anticancer activity of a clinical p38 inhibitor.	Bhattacharjee D et al.	—	2023	→
Integrative analyses highlight functional regulatory variants associated with neuropsychiatric diseases.	Guo MG et al.	—	2023	→
Interrogating colorectal cancer metastasis to liver: a search for clinically viable compounds and mechanistic insights in colorectal cancer Patient Derived Organoids.	Cioce M et al.	—	2023	→
Investigation of LGALS2 expression in the TCGA database reveals its clinical relevance in breast cancer immunotherapy and drug resistance.	He S et al.	—	2023	→
KNeMAP: a network mapping approach for knowledge-driven comparison of transcriptomic profiles.	Pavel A et al.	—	2023	→
Leveraging genetic diversity to identify small molecules that reverse mouse skeletal muscle insulin resistance.	Masson SWC et al.	—	2023	→
LncRNAs associated with vascular mimicry establish a novel molecular subtype and prognostic model for pancreatic cancer.	Li D et al.	—	2023	→
Machine learning-identified stemness features and constructed stemness-related subtype with prognosis, chemotherapy, and immunotherapy responses for non-small cell lung cancer patients.	Liu M et al.	—	2023	→
Machine learning model for anti-cancer drug combinations: Analysis, prediction, and validation.	Zhou JB et al.	—	2023	→
MAVEN: compound mechanism of action analysis and visualisation using transcriptomics and compound structure data in R/Shiny.	Hosseini-Gerami L et al.	—	2023	→
MicroRNA-Based Discovery of Biomarkers, Therapeutic Targets, and Repositioning Drugs for Breast Cancer.	Ye Q et al.	—	2023	→
Mitochondrial-Related Genes May Be an Important Factor in the Immune Microenvironment of Decompensated Cirrhosis and Acute-on-Chronic Liver Failure: New Findings Based on Double Disease Analysis	Qin Y et al.	—	2023	—
Models of KPTN-related disorder implicate mTOR signalling in cognitive and overgrowth phenotypes.	Levitin MO et al.	—	2023	→
Morphological subprofile analysis for bioactivity annotation of small molecules.	Pahl A et al.	—	2023	→
MPFFPSDC: A multi-pooling feature fusion model for predicting synergistic drug combinations.	Bao X et al.	—	2023	→
Multi-ancestry study of the genetics of problematic alcohol use in over 1 million individuals.	Zhou H et al.	—	2023	→
Multi-Omics Analysis and Verification of the Oncogenic Value of CCT8 in Pan-Cancers.	Gong L et al.	—	2023	→
Network neighborhood operates as a drug repositioning method for cancer treatment.	Cüvitoğlu A et al.	—	2023	→
Neurodegenerative Disease Associated Pathways in the Brains of Triple Transgenic Alzheimer's Model Mice Are Reversed Following Two Weeks of Peripheral Administration of Fasudil.	Killick R et al.	—	2023	→
Neurodevelopmental deficits and cell-type-specific transcriptomic perturbations in a mouse model of HNRNPU haploinsufficiency.	Dugger SA et al.	—	2023	→
Novel insights into the progression and prognosis of the calpain family members in hepatocellular carcinoma: a comprehensive integrated analysis.	Dai D et al.	—	2023	→
On the importance for drug discovery of a transnational Latin American database of natural compound structures.	Thomson TM	—	2023	→
Open MoA: revealing the mechanism of action (MoA) based on network topology and hierarchy.	Liao X et al.	—	2023	→
Orchestrating information across tissues via a novel multitask GAT framework to improve quantitative gene regulation relation modeling for survival analysis.	Duan M et al.	—	2023	→
Pan-Cancer Analysis and Validation of Opioid-Related Receptors Reveals the Immunotherapeutic Value of Toll-Like Receptor 4.	Wu S et al.	—	2023	→
Pan-cancer analysis revealing that PTPN2 is an indicator of risk stratification for acute myeloid leukemia.	Wang X et al.	—	2023	→
Pan-cancer proteogenomics connects oncogenic drivers to functional states.	Li Y et al.	—	2023	→
PATH-SURVEYOR: pathway level survival enquiry for immuno-oncology and drug repurposing.	Obermayer AN et al.	—	2023	→
PC3T: a signature-driven predictor of chemical compounds for cellular transition.	Han L et al.	—	2023	→
Personalized tumor combination therapy optimization using the single-cell transcriptome.	Tang C et al.	—	2023	→
Perturbation Analysis of a Prognostic <i>DDX3X</i>-Mediated Gene Expression Signature Identifies the Antimetastatic Potential of Chaetocin in Hepatocellular Carcinoma.	Lin TC	—	2023	→
Pharmacological approaches to understanding protein kinase signaling networks.	Stephenson EH et al.	—	2023	→
PHDs-seq: a large-scale phenotypic screening method for drug discovery through parallel multi-readout quantification.	Li J et al.	—	2023	→
Pooled Genome-Scale CRISPR Screens in Single Cells.	Schraivogel D et al.	—	2023	→
Predicting the immune microenvironment and prognosis with a anoikis - related signature in breast cancer.	Lu X et al.	—	2023	→
Prediction of multi-relational drug-gene interaction via Dynamic hyperGraph Contrastive Learning.	Tao W et al.	—	2023	→
Prognosis and Personalized In Silico Prediction of Treatment Efficacy in Cardiovascular and Chronic Kidney Disease: A Proof-of-Concept Study.	Jaimes Campos MA et al.	—	2023	→
Prognostic, Immunological, and Mutational Analysis of MTA2 in Pan-Cancer and Drug Screening for Hepatocellular Carcinoma.	Huang X et al.	—	2023	→
Projecting genetic associations through gene expression patterns highlights disease etiology and drug mechanisms.	Pividori M et al.	—	2023	→
RAGE engagement by SARS-CoV-2 enables monocyte infection and underlies COVID-19 severity.	Angioni R et al.	—	2023	→
RECOVER identifies synergistic drug combinations in vitro through sequential model optimization.	Bertin P et al.	—	2023	→
Redrawing Urokinase Receptor (uPAR) Signaling with Cancer Driver Genes for Exploring Possible Anti-Cancer Targets and Drugs.	Chang YC et al.	—	2023	→
Regulating the cell shift of endothelial cell-like myofibroblasts in pulmonary fibrosis.	Wu X et al.	—	2023	→
Retinoic Acid Receptor Is a Novel Therapeutic Target for Postoperative Cognitive Dysfunction.	Bao Y et al.	—	2023	→
Revealing hidden patterns in deep neural network feature space continuum via manifold learning.	Islam MT et al.	—	2023	→
RNA helicase DHX15 exemplifies a unique dependency in acute leukemia.	Guo H et al.	—	2023	→
Screening of immune-related secretory proteins linking chronic kidney disease with calcific aortic valve disease based on comprehensive bioinformatics analysis and machine learning.	Zhu E et al.	—	2023	→
Signature-driven repurposing of Midostaurin for combination with MEK1/2 and KRASG12C inhibitors in lung cancer.	Macaya I et al.	—	2023	→
Single-cell dissection reveals the role of aggrephagy patterns in tumor microenvironment components aiding predicting prognosis and immunotherapy on lung adenocarcinoma.	Sun X et al.	—	2023	→
SRC and TKS5 mediated podosome formation in fibroblasts promotes extracellular matrix invasion and pulmonary fibrosis.	Barbayianni I et al.	—	2023	→
Systematic transcriptional analysis of human cell lines for gene expression landscape and tumor representation.	Jin H et al.	—	2023	→
Systems immunology-based drug repurposing framework to target inflammation in atherosclerosis.	Amadori L et al.	—	2023	→
Targeting the post-synaptic proteome has therapeutic potential for psychosis in Alzheimer Disease.	Krivinko JM et al.	—	2023	→
The dawn of spatial omics.	Bressan D et al.	—	2023	→
The Marine Natural Compound Dragmacidin D Selectively Induces Apoptosis in Triple-Negative Breast Cancer Spheroids.	Guzmán EA et al.	—	2023	→
The Novel Link between Gene Expression Profiles of Adult T-Cell Leukemia/Lymphoma Patients' Peripheral Blood Lymphocytes and Ferroptosis Susceptibility.	Wang Y et al.	—	2023	→
The pharmacoepigenomic landscape of cancer cell lines reveals the epigenetic component of drug sensitivity.	Ohnmacht AJ et al.	—	2023	→
Therapeutic Effects of Combination of Nebivolol and Donepezil: Targeting Multifactorial Mechanisms in ALS.	Lee SY et al.	—	2023	→
The RNA helicase DDX39B activates FOXP3 RNA splicing to control T regulatory cell fate.	Hirano M et al.	—	2023	→
Toxicogenomics Approaches to Address Toxicity and Carcinogenicity in the Liver.	Pandiri AR et al.	—	2023	→
TRAIP serves as a potential prognostic biomarker and correlates with immune infiltrates in lung adenocarcinoma.	Jing Y et al.	—	2023	→
Transcriptional Response to Standard AML Drugs Identifies Synergistic Combinations.	More P et al.	—	2023	→
Transcriptomic clock predicts vascular changes of prodromal diabetic retinopathy.	Toh H et al.	—	2023	→
Transcriptomics, metabolomics, and in-silico drug predictions for liver damage in young and aged burn victims.	Malachowska B et al.	—	2023	→
Transfer Learning with Kernel Methods.	Radhakrishnan A et al.	—	2023	→
Tumor biology, immune infiltration and liver function define seven hepatocellular carcinoma subtypes linked to distinct drivers, survival and drug response.	Wu R et al.	—	2023	→
Understanding cancer drug resistance with <i>Sleeping Beauty</i> functional genomic screens: Application to MAPK inhibition in cutaneous melanoma.	Zhu EY et al.	—	2023	→
UNMF: a unified nonnegative matrix factorization for multi-dimensional omics data.	Abe K et al.	—	2023	→
Using graph-based model to identify cell specific synthetic lethal effects.	Pu M et al.	—	2023	→
Visceral fat percentage for prediction of outcome in uterine cervical cancer.	Eide AJ et al.	—	2023	→