Open AccessBiclustering microarray data by Gibbs sampling
Author(s) -
Qizheng Sheng,
Yves Moreau,
Bart De Moor
Publication year - 2003
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btg1078
Subject(s) - biclustering , gibbs sampling , computer science , data mining , cluster analysis , probabilistic logic , sampling (signal processing) , ranking (information retrieval) , pattern recognition (psychology) , artificial intelligence , bayesian probability , fuzzy clustering , cure data clustering algorithm , filter (signal processing) , computer vision
Gibbs sampling has become a method of choice for the discovery of noisy patterns, known as motifs, in DNA and protein sequences. Because handling noise in microarray data presents similar challenges, we have adapted this strategy to the biclustering of discretized microarray data.
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