Although it should be emphasized that many of the biological effects seen in neuropsychiatric diseases may be specific to humans, model systems will continue to serve a fundamental role in the post transcriptomic era of modern biology. For example, systematically combining multiple biological networks within a yeast reference population clearly demonstrated that integrating several datasets can improve prediction of causal regulators of complex system behavior (Zhu et al., 2008). Combining information from human and animal models can ascertain core networks affecting disease (Emilsson et al., 2008). Alternatively, animal models explicitly created for a desired attribute may be sequenced to find novel causal contributors. Studying alcohol preferring and nonpreferring rats identified a stop codon within the metabotropic glutamate receptor 2 (Grm2) that controls protein expression and alcohol-drinking behavior (Zhou et al., 2013). This is just one example of the presumably large collection of variants that will be identified in alcohol consumption, which may eventually intersect with those recognized in human populations. Identifying networks with convergent validity across model organisms and humans (Fig. 11.12) has the potential to isolate systems for therapeutic intervention tailored to the specific needs of the individual.
