In this paper, we present a methodology to take advantage of the homogeneously expressed genes in biclusters to construct a classifier for sample class ...
Jan 8, 2014 · be one of the most effective methods for discovering gene expression patterns under various conditions. In this paper, we present a framework to ...
Abstract. In gene expression microarray data analysis, biclustering has been demonstrated to be one of the most effective methods for discovering gene ex-.
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The data sets and the source code of our paper 'A Biclustering-based Classification Framework for Microarray Analysis' can be downloaded from GitHub:Bicluster ...
May 27, 2008 · ... biclustering has become one of the most popular methods for classifying data from microarrays. ... based on a ... This microarray analysis framework ...
A new algorithm is presented for fitting the plaid model, a biclustering method developed for clustering gene expression data. The approach is based on ...
This analysis of multiple input data sets leads to problem formulations which are clearly different from existing biclustering approaches based on evolutionary ...
Dec 16, 2009 · In this paper, we introduce a new enumeration algorithm for biclustering of DNA microarray data, called BiMine. Our algorithm is based on three ...
Jun 9, 2009 · A mixture model-based approach to the clustering of microarray expression data. Bioinformatics. 2002;18:413–422. [PubMed] [Google Scholar]. 3 ...
Global analyses of RNA expression levels are useful for classifying genes and overall phenotypes. Often these classification problems are linked, ...