• DocumentCode
    688531
  • Title

    Reconstruction of gene regulatory network of colon cancer using information theoretic approach

  • Author

    Raza, Khurram ; Parveen, Rafat

  • Author_Institution
    Dept. of Comput. Sci., Central Univ., New Delhi, India
  • fYear
    2013
  • fDate
    26-27 Sept. 2013
  • Firstpage
    461
  • Lastpage
    466
  • Abstract
    Reconstruction of gene regulatory networks or ´reverse-engineering´ is a process of identifying gene interaction networks from experimental microarray gene expression profile through computation techniques. In this paper, we tried to reconstruct cancer-specific gene regulatory network using information theoretic approach - mutual information. The considered microarray data consists of large number of genes with 20 samples-12 samples from colon cancer patient and 8 from normal cell. The data has been preprocessed and normalized. A t-test statistics has been applied to filter differentially expressed genes. The interaction between filtered genes has been computed using mutual information and ten different networks has been constructed with varying number of interactions ranging from 30 to 500. We performed the topological analysis of the reconstructed network, revealing a large number of interactions in colon cancer. Finally, validation of the inferred results has been done with available biological databases and literature.
  • Keywords
    cancer; medical computing; statistical testing; biological databases; cancer-specific gene regulatory network reconstruction; colon cancer patient; gene interaction networks; information theoretic approach; microarray data; microarray gene expression profile; mutual information; reverse-engineering; t-test statistics; topological analysis; Gene regulatory networks; colon cancer; microarray; systems biology;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Confluence 2013: The Next Generation Information Technology Summit (4th International Conference)
  • Conference_Location
    Noida
  • Electronic_ISBN
    978-1-84919-846-2
  • Type

    conf

  • DOI
    10.1049/cp.2013.2357
  • Filename
    6832373