{"title":"Mining coregulated biclusters from gene expression data","authors":"K. I. Lakshmi, C. P. Chandran","doi":"10.1109/ICPRIME.2012.6208292","DOIUrl":null,"url":null,"abstract":"The objective of this paper is mining coregulated biclusters from gene expression data. Gene expression is the process which produces functional product from the gene information. Data mining is used to find relevant and useful information from databases. Clustering groups the genes according to the given conditions. Biclustering algorithms belong to a distinct class of clustering algorithms that perform simultaneous clustering of both rows and columns of the gene expression matrix. In this paper a new algorithm, Enhanced Bimax algorithm is proposed based on the Bimax algorithm [7]. The normalization technique is included which is used to display a coregulated biclusters from gene expression data and grouping the genes in the particular order. In this work, Synthetic dataset is used to display the coregulated genes.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPRIME.2012.6208292","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The objective of this paper is mining coregulated biclusters from gene expression data. Gene expression is the process which produces functional product from the gene information. Data mining is used to find relevant and useful information from databases. Clustering groups the genes according to the given conditions. Biclustering algorithms belong to a distinct class of clustering algorithms that perform simultaneous clustering of both rows and columns of the gene expression matrix. In this paper a new algorithm, Enhanced Bimax algorithm is proposed based on the Bimax algorithm [7]. The normalization technique is included which is used to display a coregulated biclusters from gene expression data and grouping the genes in the particular order. In this work, Synthetic dataset is used to display the coregulated genes.