Paper Title:
Mining Maximal Dense Subgraphs in Uncertain PPI Network
  Abstract

Several studies have shown that the prediction of protein function using PPI data is promising. However, the PPI data generated from experiments are noisy, incomplete and inaccurate, which promotes to represent PPI dataset as an uncertain graph. In this paper, we proposed a novel algorithm to mine maximal dense subgraphs efficiently in uncertain PPI network. It adopted several techniques to achieve efficient mining. An extensive experimental evaluation on yeast PPI network demonstrated that our approach had good performance in terms of precision and efficiency.

  Info
Periodical
Chapter
Chapter 5: Information Technology
Edited by
Robin G. Qiu and Yongfeng Ju
Pages
609-615
DOI
10.4028/www.scientific.net/AMM.135-136.609
Citation
J. C. Liu, X. Q. Shang, Y. Meng, M. Wang, "Mining Maximal Dense Subgraphs in Uncertain PPI Network", Applied Mechanics and Materials, Vols. 135-136, pp. 609-615, 2012
Online since
October 2011
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