An interaction pattern kernel approach for protein-protein interaction extraction from biomedical literature

Yung Chun Chang, Yu Chen Su, Nai Wen Chang, Wen Lian Hsu

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Discovering the interactions between proteins mentioned in biomedical literature is one of the core topics of text mining in the life sciences. In this paper, we propose an interaction pattern generation approach to capture frequent PPI patterns in text. We also present an interaction pattern tree kernel method that integrates the PPI pattern with convolution tree kernel to extract protein-protein interactions. Empirical evaluations on LLL, IEPA, and HPRD50 corpora demonstrate that our method is effective and outperforms several wellknown PPI extraction methods.

Original languageEnglish
Pages (from-to)36-46
Number of pages11
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8916
Publication statusPublished - 2014
Externally publishedYes

Fingerprint

Protein-protein Interaction
kernel
Proteins
Interaction
Frequent Pattern
Life sciences
Text Mining
Kernel Methods
Convolution
Integrate
Protein
Evaluation
Demonstrate

Keywords

  • Interaction pattern generation
  • Interaction pattern tree kernel
  • Protein-protein interaction
  • Text mining

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

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abstract = "Discovering the interactions between proteins mentioned in biomedical literature is one of the core topics of text mining in the life sciences. In this paper, we propose an interaction pattern generation approach to capture frequent PPI patterns in text. We also present an interaction pattern tree kernel method that integrates the PPI pattern with convolution tree kernel to extract protein-protein interactions. Empirical evaluations on LLL, IEPA, and HPRD50 corpora demonstrate that our method is effective and outperforms several wellknown PPI extraction methods.",
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AB - Discovering the interactions between proteins mentioned in biomedical literature is one of the core topics of text mining in the life sciences. In this paper, we propose an interaction pattern generation approach to capture frequent PPI patterns in text. We also present an interaction pattern tree kernel method that integrates the PPI pattern with convolution tree kernel to extract protein-protein interactions. Empirical evaluations on LLL, IEPA, and HPRD50 corpora demonstrate that our method is effective and outperforms several wellknown PPI extraction methods.

KW - Interaction pattern generation

KW - Interaction pattern tree kernel

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KW - Text mining

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