Technological advancements in the field of genetics have led not only to an abundance of experimental data, but also caused an\r\nexponential increase of the number of published biomolecular studies. Text mining is widely accepted as a promising technique\r\nto help researchers in the life sciences deal with the amount of available literature. This paper presents a freely available web\r\napplication built on top of 21.3 million detailed biomolecular events extracted from all PubMed abstracts. These text mining\r\nresults were generated by a state-of-the-art event extraction system and enriched with gene family associations and abstract\r\ngeneralizations, accounting for lexical variants and synonymy. The EVEX resource locates relevant literature on phosphorylation,\r\nregulation targets, binding partners, and several other biomolecular events and assigns confidence values to these events. The\r\nsearch function accepts official gene/protein symbols as well as common names from all species. Finally, the web application is a\r\npowerful tool for generating homology-based hypotheses as well as novel, indirect associations between genes and proteins such\r\nas coregulators.
Loading....