title: A network partition algorithm for mining gene functional modules of colon cancer from DNA microarray data.
abstract: Computational analysis is essential for transforming the masses of microarray data into a mechanistic understanding of cancer. Here we present a method for finding gene functional modules of cancer from microarray data and have applied it to colon cancer. First, a colon cancer gene network and a normal colon tissue gene network were constructed using correlations between the genes. Then the modules that tended to have a homogeneous functional composition were identified by splitting up the network. Analysis of both networks revealed that they are scale-free. Comparison of the gene functional modules for colon cancer and normal tissues showed that the modules' functions changed with their structures.
authors.affiliation: Institute of Artificial Intelligence and Robotics, School of Electronic Information & Control Engineering, Beijing University of Technology, Beijing 100022, China.
authors.forename: Xiao-Gang
authors.initials: XG
authors.lastname: Ruan
authors.forename: Jin-Lian
authors.initials: JL
authors.lastname: Wang
authors.forename: Jian-Geng
authors.initials: JG
authors.lastname: Li
mesh_terms: D000465:Algorithms; D003110:Colonic Neoplasms / Q000378:metabolism*; D053263:Gene Regulatory Networks; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*