PPI-IRO: A two-stage method for protein-protein interaction extraction based on interaction relation ontology

Handle URI:
http://hdl.handle.net/10754/563219
Title:
PPI-IRO: A two-stage method for protein-protein interaction extraction based on interaction relation ontology
Authors:
Li, Chuanxi; Chen, Peng; Wang, Rujing; Wang, Xiujie; Su, Yaru; Li, Jinyan
Abstract:
Mining Protein-Protein Interactions (PPIs) from the fast-growing biomedical literature resources has been proven as an effective approach for the identifi cation of biological regulatory networks. This paper presents a novel method based on the idea of Interaction Relation Ontology (IRO), which specifi es and organises words of various proteins interaction relationships. Our method is a two-stage PPI extraction method. At fi rst, IRO is applied in a binary classifi er to determine whether sentences contain a relation or not. Then, IRO is taken to guide PPI extraction by building sentence dependency parse tree. Comprehensive and quantitative evaluations and detailed analyses are used to demonstrate the signifi cant performance of IRO on relation sentences classifi cation and PPI extraction. Our PPI extraction method yielded a recall of around 80% and 90% and an F1 of around 54% and 66% on corpora of AIMed and Bioinfer, respectively, which are superior to most existing extraction methods. Copyright © 2014 Inderscience Enterprises Ltd.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Publisher:
Inderscience Publishers
Journal:
International Journal of Data Mining and Bioinformatics
Issue Date:
2014
DOI:
10.1504/IJDMB.2014.062890
Type:
Article
ISSN:
17485673
Sponsors:
We thank the anonymous reviewers for their constructive comments on the paper. This research was supported in part by the National Natural Science Foundation of China (No. 60774096) and the National Key Technology R&D Program of China (No. 2008BAK49B05). This work was also supported in party by the National Science Foundation of China (No. 60803107).
Appears in Collections:
Articles; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorLi, Chuanxien
dc.contributor.authorChen, Pengen
dc.contributor.authorWang, Rujingen
dc.contributor.authorWang, Xiujieen
dc.contributor.authorSu, Yaruen
dc.contributor.authorLi, Jinyanen
dc.date.accessioned2015-08-03T11:43:26Zen
dc.date.available2015-08-03T11:43:26Zen
dc.date.issued2014en
dc.identifier.issn17485673en
dc.identifier.doi10.1504/IJDMB.2014.062890en
dc.identifier.urihttp://hdl.handle.net/10754/563219en
dc.description.abstractMining Protein-Protein Interactions (PPIs) from the fast-growing biomedical literature resources has been proven as an effective approach for the identifi cation of biological regulatory networks. This paper presents a novel method based on the idea of Interaction Relation Ontology (IRO), which specifi es and organises words of various proteins interaction relationships. Our method is a two-stage PPI extraction method. At fi rst, IRO is applied in a binary classifi er to determine whether sentences contain a relation or not. Then, IRO is taken to guide PPI extraction by building sentence dependency parse tree. Comprehensive and quantitative evaluations and detailed analyses are used to demonstrate the signifi cant performance of IRO on relation sentences classifi cation and PPI extraction. Our PPI extraction method yielded a recall of around 80% and 90% and an F1 of around 54% and 66% on corpora of AIMed and Bioinfer, respectively, which are superior to most existing extraction methods. Copyright © 2014 Inderscience Enterprises Ltd.en
dc.description.sponsorshipWe thank the anonymous reviewers for their constructive comments on the paper. This research was supported in part by the National Natural Science Foundation of China (No. 60774096) and the National Key Technology R&D Program of China (No. 2008BAK49B05). This work was also supported in party by the National Science Foundation of China (No. 60803107).en
dc.publisherInderscience Publishersen
dc.subjectBioinformaticsen
dc.subjectInformation extractionen
dc.subjectInteraction relation ontologyen
dc.subjectProtein-protein interactionen
dc.subjectRelation extractionen
dc.subjectRelation worden
dc.subjectSentence typed dependencyen
dc.subjectText miningen
dc.titlePPI-IRO: A two-stage method for protein-protein interaction extraction based on interaction relation ontologyen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalInternational Journal of Data Mining and Bioinformaticsen
dc.contributor.institutionInstitute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, Chinaen
dc.contributor.institutionSchool of Information Science and Technology, University of Science and Technology of China, Hefei 230026, Chinaen
dc.contributor.institutionState Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, Chinaen
dc.contributor.institutionAdvanced Analytics Institute, University of Technology Sydney, Australiaen
kaust.authorChen, Pengen
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