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An Efficient Convex Nonnegative Network Component Analysis for Gene Regulatory Network Reconstruction

  • Jisheng Dai
  • Chunqi Chang
  • Zhongfu Ye
  • Yeung Sam Hung
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5780)

Abstract

A systems biology problem of reconstructing gene regulatory network from time-course gene expression microarray data via network component analysis (NCA) is investigated in this paper. Inspired by the idea that each column of the connectivity matrix can be estimated independently, we try to propose a fast and stable convex approach for nonnegative NCA (nnNCA). Compared with the existing method, our new method reduces the computational cost substantially, whereas maintains a reasonable accuracy. Both the simulation results and experimental results demonstrate the effectiveness of our method.

Keywords

Gene regulatory network microarray network component analysis convex programming positivity constraints 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Jisheng Dai
    • 1
    • 2
  • Chunqi Chang
    • 1
  • Zhongfu Ye
    • 2
  • Yeung Sam Hung
    • 1
  1. 1.Department of Electrical and Electronic EngineeringThe University of Hong KongHong Kong
  2. 2.Department of Electronic Engineering and Information ScienceUniversity of Science and Technology of ChinaHefeiP.R. China

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