A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is
IEEE/SP 13th Workshop on Statistical Signal Processing, 2005
Recently, biclustering algorithms have been used to extract useful information from large sets of DNA microarray experimental data. They refer to a distinct class of clustering algorithms that perform simultaneous row-column clustering. The goal is to find submatrices, that is, subgroups of genes and subgroups of conditions, where the genes exhibit highly correlated activities for every condition. Almost all of the methods proposed in the literature search for one or two types of biclusterdoi:10.1109/ssp.2005.1628738 fatcat:geohuhmfnrd3fn2z3kb43lfwgi