Quality measures for gene expression biclusters

PloS One
Beatriz PontesJess S Aguilar-Ruiz

Abstract

An noticeable number of biclustering approaches have been proposed proposed for the study of gene expression data, especially for discovering functionally related gene sets under different subsets of experimental conditions. In this context, recognizing groups of co-expressed or co-regulated genes, that is, genes which follow a similar expression pattern, is one of the main objectives. Due to the problem complexity, heuristic searches are usually used instead of exhaustive algorithms. Furthermore, most of biclustering approaches use a measure or cost function that determines the quality of biclusters. Having a suitable quality metric for bicluster is a critical aspect, not only for guiding the search, but also for establishing a comparison criteria among the results obtained by different biclustering techniques. In this paper, we analyse a large number of existing approaches to quality measures for gene expression biclusters, as well as we present a comparative study of them based on their capability to recognize different expression patterns in biclusters.

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Citations

Nov 8, 2015·Journal of Cardiovascular Translational Research·Ares Pasipoularides
Jul 15, 2015·Journal of Biomedical Informatics·Beatriz PontesJesús S Aguilar-Ruiz
May 24, 2018·Bioinformatics·Patryk OrzechowskiJason H Moore
Sep 27, 2018··Pornpimol ChaiwuttisakLaetitia Jourdan

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Software Mentioned

MSA
Evo
Steminal
VE
Virtual Error ( VE
SMSR
Bexpa
MSR
EvoBexpa

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