A bottom-up approach to the biclustering-problem.
The biclustering problem adresses the discovery of locally significant correlation within a data matrix and has recently become quite popular in the field of microarray data analysis. The preservation of a particularly defined degree of homogeneity between elements within a bicluster plays a key role in the search procedure. This work proposes a pairwise distance function related to the mean squared residue to introduce multiple enrichment algorithms. Based on a theoretical framework, the impact is demonstrated empirically by the enrichment of commonly available and also on artificially generated bicluster sets.
Koh
Hyung-Won
HW
ISAS - Institute for Analytical Sciences, Dortmund, Germany. koh@isas.de
Hildebrand
Lars
L
D000465:Algorithms; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods; D057225:Data Mining / Q000379:methods; D020869:Gene Expression Profiling / Q000379:methods*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*