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

Rajesh Chowdhary; Jinfeng Zhang; Sinlam Tan; Daniel E. Osborne; Vladimir B. Bajic; Jun Liu

doi:10.1504/IJDMB.2013.054232

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

Rajesh Chowdhary, Jinfeng Zhang, Sinlam Tan, Daniel E. Osborne, Vladimir B. Bajic, Jun Liu

Research output: Contribution to journal › Article › peer-review

13 Scopus citations

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. Copyright © 2013 Inderscience Enterprises Ltd.

Original language	English (US)
Pages (from-to)	450
Journal	International Journal of Data Mining and Bioinformatics
Volume	7
Issue number	4
DOIs	https://doi.org/10.1504/IJDMB.2013.054232
State	Published - 2013

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This 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.

ASJC Scopus subject areas

General Biochemistry, Genetics and Molecular Biology
Library and Information Sciences
Information Systems

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10.1504/IJDMB.2013.054232

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@article{f684b81415f34cdfb2a692a0c2193697,

title = "PIMiner: A web tool for extraction of protein interactions from biomedical literature",

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. Copyright {\textcopyright} 2013 Inderscience Enterprises Ltd.",

author = "Rajesh Chowdhary and Jinfeng Zhang and Sinlam Tan and Osborne, {Daniel E.} and Bajic, {Vladimir B.} and Jun Liu",

note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: This 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.",

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AU - Osborne, Daniel E.

AU - Bajic, Vladimir B.

AU - Liu, Jun

N1 - KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: This 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.

PY - 2013

Y1 - 2013

N2 - 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. Copyright © 2013 Inderscience Enterprises Ltd.

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

Abstract

Bibliographical note

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