Large-scale extraction of gene interactions from full-text literature using DeepDive.
BACKGROUND
A complete repository of gene-gene interactions is key for understanding cellular processes, human disease and drug response. These gene-gene interactions include both protein-protein interactions and transcription factor interactions. The majority of known interactions are found in the biomedical literature. Interaction databases, such as BioGRID and ChEA, annotate these gene-gene interactions; however, curation becomes difficult as the literature grows exponentially. DeepDive is a trained system for extracting information from a variety of sources, including text. In this work, we used DeepDive to extract both protein-protein and transcription factor interactions from over 100,000 full-text PLOS articles.


METHODS
We built an extractor for gene-gene interactions that identified candidate gene-gene relations within an input sentence. For each candidate relation, DeepDive computed a probability that the relation was a correct interaction. We evaluated this system against the Database of Interacting Proteins and against randomly curated extractions.


RESULTS
Our system achieved 76% precision and 49% recall in extracting direct and indirect interactions involving gene symbols co-occurring in a sentence. For randomly curated extractions, the system achieved between 62% and 83% precision based on direct or indirect interactions, as well as sentence-level and document-level precision. Overall, our system extracted 3356 unique gene pairs using 724 features from over 100,000 full-text articles.


METHODS
Application source code is publicly available at https://github.com/edoughty/deepdive_genegene_app


BACKGROUND
russ.altman@stanford.edu


BACKGROUND
Supplementary data are available at Bioinformatics online.
Biomedical Informatics Training Program, Stanford University, Stanford, CA 94305, USA.
Emily K
EK
Mallory
Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA.
Ce
C
Zhang
Department of Computer Science.
Christopher
C
Ré
Department of Bioengineering, Department of Genetics and Department of Medicine, Stanford University, Stanford, CA 94305, USA.
Russ B
RB
Altman
D066289:Data Curation; D057225:Data Mining; D030541:Databases, Genetic; D004843:Epistasis, Genetic; D006801:Humans; D016247:Information Storage and Retrieval; D011642:Publications; D012984:Software