A variety of other computational methods are being developed to automatically extract information from the literature. These methods range from simple technologies which process at the word level and require only a limited linguistic context [11] to state-of-art technologies such as natural language processing (NLP) that handle more complex relations across sentences [12]. So far, these methods have not been used extensively in generally available pathway interfaces. A number of groups, including the Ingenuity Pathway database [13] and the Protein Reference Database [14,15], are developing mammalian pathway descriptions by means of manual curation of the literature. Although these databases provide rather precise data, the human-curation process makes development slow. This problem is becoming more serious as the size of the relevant literature increases. Protein interaction networks have also been built automatically [16-19], using probability models to integrate data from high throughput experiments such as yeast-2-hybrid [20,21] and TAP pull-downs [22].
