PIMiner: a web tool for extraction of protein interactions from biomedical literature

Authors:
Rajesh Chowdhary;Jinfeng Zhang;Sin Lam Tan;Daniel E. Osborne;Vladimir B. Bajic;Jun S. Liu
Affiliations:
Biomedical Informatifcs Research Center, MCRF, Marshfield Clinic, 1000 North Oak Avenue, Marshfield, WI 54449, USA;Department of Statistics, Florida State University, Tallahassee, FL 32306, USA;Biomedical Informatics Research Center, MCRF, Marshfield Clinic, 1000 North Oak Avenue, Marshfield, WI 54449, USA;Department of Statistics, Florida State University, Tallahassee, FL 32306, USA;Computational Bioscience Research Center CBRC, King Abdullah University of Science and Technology KAUST, Thuwal 23955-6900, Kingdom of Saudi Arabia;Department of Statistics, Harvard University, Cambridge, MA 02138, USA
Venue:
International Journal of Data Mining and Bioinformatics
Year:
2013

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Abstract

Information on Protein Interactions PIs is valuable for biomedical research, but often lies buried in the scientific literature and cannot be readily retrieved. While much progress has been made over the years in extracting PIs from the literature using computational methods, there is a lack of free, public, user-friendly tools for the discovery of PIs. We developed an online tool for the extraction of PI relationships from PubMed-abstracts, which we name PIMiner. Protein pairs and the words that describe their interactions are reported by PIMiner so that new interactions can be easily detected within text. The interaction likelihood levels are reported too. The option to extract only specific types of interactions is also provided. The PIMiner server can be accessed through a web browser or remotely through a client's command line. PIMiner can process 50,000 PubMed abstracts in approximately 7 min and thus appears suitable for large-scale processing of biological/biomedical literature.