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Topology association analysis in weighted protein interaction network for gene prioritization

Author

Listed:
  • Wu, Shunyao
  • Shao, Fengjing
  • Zhang, Qi
  • Ji, Jun
  • Xu, Shaojie
  • Sun, Rencheng
  • Sun, Gengxin
  • Du, Xiangjun
  • Sui, Yi

Abstract

Although lots of algorithms for disease gene prediction have been proposed, the weights of edges are rarely taken into account. In this paper, the strengths of topology associations between disease and essential genes are analyzed in weighted protein interaction network. Empirical analysis demonstrates that compared to other genes, disease genes are weakly connected with essential genes in protein interaction network. Based on this finding, a novel global distance measurement for gene prioritization with weighted protein interaction network is proposed in this paper. Positive and negative flow is allocated to disease and essential genes, respectively. Additionally network propagation model is extended for weighted network. Experimental results on 110 diseases verify the effectiveness and potential of the proposed measurement. Moreover, weak links play more important role than strong links for gene prioritization, which is meaningful to deeply understand protein interaction network.

Suggested Citation

  • Wu, Shunyao & Shao, Fengjing & Zhang, Qi & Ji, Jun & Xu, Shaojie & Sun, Rencheng & Sun, Gengxin & Du, Xiangjun & Sui, Yi, 2016. "Topology association analysis in weighted protein interaction network for gene prioritization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 262-269.
    • Handle: RePEc:eee:phsmap:v:461:y:2016:i:c:p:262-269
    DOI: 10.1016/j.physa.2016.05.043
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