PIMiner: A web tool for extraction of protein interactions from biomedical literature
KAUST DepartmentComputational Bioscience Research Center (CBRC)
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Applied Mathematics and Computational Science Program
Permanent link to this recordhttp://hdl.handle.net/10754/562510
MetadataShow full item record
AbstractInformation 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. Copyright © 2013 Inderscience Enterprises Ltd.
CitationChowdhary, R., Zhang, J., Tan, S. L., Osborne, D. E., Bajic, V. B., & Liu, J. S. (2013). PIMiner: a web tool for extraction of protein interactions from biomedical literature. International Journal of Data Mining and Bioinformatics, 7(4), 450. doi:10.1504/ijdmb.2013.054232
SponsorsThis study was supported in part by grant 1UL1RR025011 from the Clinical and Translational Science Award (CTSA) program of the National Center for Research Resources, National Institutes of Health. We thank Ryan Frahm for providing server support. We also sincerely thank Rachel V. Stankowski for proof-reading the manuscript and for her comments.
PubMed Central IDPMC4303605
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