Inferring Protein-Protein Interactions Based on Sequences and Interologs in Mycobacterium Tuberculosis

  • Zhi-Ping Liu
  • Jiguang Wang
  • Yu-Qing Qiu
  • Ross K. K. Leung
  • Xiang-Sun Zhang
  • Stephen K. W. Tsui
  • Luonan Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6840)

Abstract

Mycobacterium tuberculosis is a pathogenic bacterium that poses serious threat to human health. Inference of the protein interactions of M. tuberculosis will provide cues to understand the biological processes in this pathogen. In this paper, we constructed an integrated M. tuberculosis H37Rv protein interaction network by machine learning and ortholog-based methods. Firstly, we developed a support vector machine (SVM) method to infer the protein interactions by gene sequence information. We tested our predictors in Escherichia coli and mapped the genetic codon features underlying protein interactions to M. tuberculosis. Moreover, the documented interactions of other 14 species were mapped to the proteome of M. tuberculosis by the interolog method. The ensemble protein interactions were then validated by various functional linkages i.e., gene coexpression, evolutionary relationship and functional similarity, extracted from heterogeneous data sources.

Keywords

Protein Interaction Functional Similarity Protein Interaction Network Semantic Similarity Measure Heterogeneous Data Source 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Zhi-Ping Liu
    • 1
  • Jiguang Wang
    • 2
  • Yu-Qing Qiu
    • 3
  • Ross K. K. Leung
    • 4
  • Xiang-Sun Zhang
    • 3
  • Stephen K. W. Tsui
    • 4
  • Luonan Chen
    • 1
  1. 1.Key Laboratory of Systems BiologyShanghai Institutes for Biological Sciences, Chinese Academy of SciencesChina
  2. 2.Beijing Institute of GenomicsChinese Academy of SciencesChina
  3. 3.Academy of Mathematics and Systems ScienceChinese Academy of SciencesChina
  4. 4.Hong Kong Bioinformatics CentreThe Chinese University of Hong KongShatin N. T.China

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