An Improved Biclustering Algorithm for Gene Expression Data

摘要

Cheng-Church (CC) biclustering algorithm is the popular algorithm for the gene expression data mining at present.Only find one biclustering can be found at one time and the biclustering that overlap each other can hardly be foundwhen using this algorithm. This article puts forward a modified algorithm for the gene expression data mining that usesthe middle biclustering result to conduct the randomization process, digging up more eligible biclustering data. It alsoraised a parallel computing method that uses the multi-core processor or cluster environment to improve efficiency. It isproved by experimental verification that the modified algorithm enhances the precision and efficiency of the gene expressiondata mining to a certain degree.