Co-clustering: a versatile tool for data analysis in biomedical informatics.
Co-clustering has not been much exploited in biomedical informatics, despite its success in other domains. Most of the previous applications were limited to analyzing gene expression data. We performed co-clustering analysis on other types of data and obtained promising results, as summarized in this paper.
Computer Systems Laboratory, Stanford University, Stanford, CA 94305, USA. sryoon@gmail.com
Sungroh
S
Yoon
Luca
L
Benini
Giovanni
G
De Micheli
D000465:Algorithms; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D017422:Sequence Analysis, DNA / Q000379:methods*; D017423:Sequence Analysis, RNA / Q000379:methods*