IntEx: A syntactic role driven protein-protein interaction extractor for bio-medical text

Syed Toufeeq Ahmed; Deepthi Chidambaram; Hasan Davulcu; Chitta Baral

IntEx: A syntactic role driven protein-protein interaction extractor for bio-medical text

Syed Toufeeq Ahmed, Deepthi Chidambaram, Hasan Davulcu, Chitta Baral

Research output: Contribution to conference › Paper › peer-review

Abstract

In this paper, we present a fully automated extraction system, named IntEx, to identify gene and protein interactions in biomedical text. Our approach is based on first splitting complex sentences into simple clausal structures made up of syntactic roles. Then, tagging biological entities with the help of biomedical and linguistic ontologies. Finally, extracting complete interactions by analyzing the matching contents of syntactic roles and their linguistically significant combinations. Our extraction system handles complex sentences and extracts multiple and nested interactions specified in a sentence. Experimental evaluations with two other state of the art extraction systems indicate that the IntEx system achieves better performance without the labor intensive pattern engineering requirement.

Original language	English (US)
Pages	54-61
Number of pages	8
State	Published - 2005
Event	2005 ACL-ISMB Workshop on Linking Biological Literature, Ontologies and Databases: Mining Biological Semantics, ACL-ISMB 2005 - Detroit, United States Duration: Jun 24 2005 → …

Conference

Conference	2005 ACL-ISMB Workshop on Linking Biological Literature, Ontologies and Databases: Mining Biological Semantics, ACL-ISMB 2005
Country/Territory	United States
City	Detroit
Period	6/24/05 → …

ASJC Scopus subject areas

Biochemistry, Genetics and Molecular Biology(all)
Artificial Intelligence
Information Systems

Cite this

IntEx: A syntactic role driven protein-protein interaction extractor for bio-medical text. / Ahmed, Syed Toufeeq; Chidambaram, Deepthi; Davulcu, Hasan et al.
2005. 54-61 Paper presented at 2005 ACL-ISMB Workshop on Linking Biological Literature, Ontologies and Databases: Mining Biological Semantics, ACL-ISMB 2005, Detroit, United States.

Research output: Contribution to conference › Paper › peer-review

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abstract = "In this paper, we present a fully automated extraction system, named IntEx, to identify gene and protein interactions in biomedical text. Our approach is based on first splitting complex sentences into simple clausal structures made up of syntactic roles. Then, tagging biological entities with the help of biomedical and linguistic ontologies. Finally, extracting complete interactions by analyzing the matching contents of syntactic roles and their linguistically significant combinations. Our extraction system handles complex sentences and extracts multiple and nested interactions specified in a sentence. Experimental evaluations with two other state of the art extraction systems indicate that the IntEx system achieves better performance without the labor intensive pattern engineering requirement.",

author = "Ahmed, {Syed Toufeeq} and Deepthi Chidambaram and Hasan Davulcu and Chitta Baral",

note = "Funding Information: We would like to thank to both Dr. David Corney and Dr. Andrew Rzhetsky for sharing their evaluation datasets and results. Publisher Copyright: {\textcopyright} 2005 Association for Computational Linguistics; 2005 ACL-ISMB Workshop on Linking Biological Literature, Ontologies and Databases: Mining Biological Semantics, ACL-ISMB 2005 ; Conference date: 24-06-2005",

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AU - Chidambaram, Deepthi

AU - Davulcu, Hasan

AU - Baral, Chitta

N1 - Funding Information: We would like to thank to both Dr. David Corney and Dr. Andrew Rzhetsky for sharing their evaluation datasets and results. Publisher Copyright: © 2005 Association for Computational Linguistics

PY - 2005

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N2 - In this paper, we present a fully automated extraction system, named IntEx, to identify gene and protein interactions in biomedical text. Our approach is based on first splitting complex sentences into simple clausal structures made up of syntactic roles. Then, tagging biological entities with the help of biomedical and linguistic ontologies. Finally, extracting complete interactions by analyzing the matching contents of syntactic roles and their linguistically significant combinations. Our extraction system handles complex sentences and extracts multiple and nested interactions specified in a sentence. Experimental evaluations with two other state of the art extraction systems indicate that the IntEx system achieves better performance without the labor intensive pattern engineering requirement.

AB - In this paper, we present a fully automated extraction system, named IntEx, to identify gene and protein interactions in biomedical text. Our approach is based on first splitting complex sentences into simple clausal structures made up of syntactic roles. Then, tagging biological entities with the help of biomedical and linguistic ontologies. Finally, extracting complete interactions by analyzing the matching contents of syntactic roles and their linguistically significant combinations. Our extraction system handles complex sentences and extracts multiple and nested interactions specified in a sentence. Experimental evaluations with two other state of the art extraction systems indicate that the IntEx system achieves better performance without the labor intensive pattern engineering requirement.

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IntEx: A syntactic role driven protein-protein interaction extractor for bio-medical text

Abstract

Conference

ASJC Scopus subject areas

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