GeneNetMiner: accurately mining gene regulatory networks from literature

Lots of gene regulatory relationships have been reported derived 'small-scale' studies. These relations are buried in literature which is rapidly growing. It is extremely time-consuming and cost-intensive to manually curate gene regulatory relationships by human-reading articles. Therefore, a tool for prioritizing these relations and assisting manual curation is useful for finding gene regulatory relationships which could be used for constructing gene regulatory networks. GeneNetMiner is standalone software which parses the sentences of iHOP (Information Hyperlinked over Protein) and captures regulatory relations. The regulatory relations are either gene-gene regulations or gene-biological processes (i.e., Gene A induces cancer metastasis) relations. Capturing of gene-biological process relations is a unique feature for the tools of this kind. These relations can be used to build up gene regulatory networks for specific biological processes, diseases, or phenotypes. Users are able to search genes and biological processes to find the regulatory relationships between them. Each regulatory relationship has been assigned a confidence score, which indicates the probability of the 'true' relation. Furthermore, it reports the sentence containing the queried terms, which allows users to manually checking whether the relation is true if they wish. GeneNetMiner is able to accurately capture the regulatory relationships between genes from literature. The