A framework of integrating gene relations from heterogeneous data sources: an experiment on Arabidopsis thaliana

  • Authors:

  • Jiexun Li;Xin Li;Hua Su;Hsinchun Chen;David W. Galbraith

  • Affiliations:

  • Department of Management Information Systems, University of Arizona Tucson, AZ 85721, USA;Department of Management Information Systems, University of Arizona Tucson, AZ 85721, USA;Department of Management Information Systems, University of Arizona Tucson, AZ 85721, USA;Department of Management Information Systems, University of Arizona Tucson, AZ 85721, USA;Department of Plant Sciences, University of Arizona Tucson, AZ 85721, USA

  • Venue:
  • Bioinformatics
  • Year:
  • 2006

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Abstract

One of the most important goals of biological investigation is to uncover gene functional relations. In this study we propose a framework for extraction and integration of gene functional relations from diverse biological data sources, including gene expression data, biological literature and genomic sequence information. We introduce a two-layered Bayesian network approach to integrate relations from multiple sources into a genome-wide functional network. An experimental study was conducted on a test-bed of Arabidopsis thaliana. Evaluation of the integrated network demonstrated that relation integration could improve the reliability of relations by combining evidence from different data sources. Domain expert judgments on the gene functional clusters in the network confirmed the validity of our approach for relation integration and network inference. Contact: jiexun@eller.arizona.edu