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AIIA
2009
Springer
14 years 2 months ago
Ontology-Driven Co-clustering of Gene Expression Data
Abstract. The huge volume of gene expression data produced by microarrays and other high-throughput techniques has encouraged the development of new computational techniques to eva...
Francesca Cordero, Ruggero G. Pensa, Alessia Visco...
SDM
2007
SIAM
98views Data Mining» more  SDM 2007»
13 years 9 months ago
Lattice based Clustering of Temporal Gene-Expression Matrices
Individuals show different cell classes when they are in the different stages of a disease, have different disease subtypes, or have different response to a treatment or envir...
Yang Huang, Martin Farach-Colton
KDD
2009
ACM
229views Data Mining» more  KDD 2009»
14 years 8 months ago
An association analysis approach to biclustering
The discovery of biclusters, which denote groups of items that show coherent values across a subset of all the transactions in a data set, is an important type of analysis perform...
Gaurav Pandey, Gowtham Atluri, Michael Steinbach, ...
BMCBI
2004
229views more  BMCBI 2004»
13 years 7 months ago
Automatic annotation of protein motif function with Gene Ontology terms
Background: Conserved protein sequence motifs are short stretches of amino acid sequence patterns that potentially encode the function of proteins. Several sequence pattern search...
Xinghua Lu, Chengxiang Zhai, Vanathi Gopalakrishna...
TCBB
2008
107views more  TCBB 2008»
13 years 7 months ago
Coclustering of Human Cancer Microarrays Using Minimum Sum-Squared Residue Coclustering
It is a consensus in microarray analysis that identifying potential local patterns, characterized by coherent groups of genes and conditions, may shed light on the discovery of pre...
Hyuk Cho, Inderjit S. Dhillon