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BMCBI
2006
170views more  BMCBI 2006»
13 years 5 months ago
Biclustering of gene expression data by non-smooth non-negative matrix factorization
Background: The extended use of microarray technologies has enabled the generation and accumulation of gene expression datasets that contain expression levels of thousands of gene...
Pedro Carmona-Saez, Roberto D. Pascual-Marqui, Fra...
KDD
2009
ACM
229views Data Mining» more  KDD 2009»
14 years 5 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, ...
CPM
2004
Springer
110views Combinatorics» more  CPM 2004»
13 years 10 months ago
Finding Biclusters by Random Projections
Given a matrix X composed of symbols, a bicluster is a submatrix of X obtained by removing some of the rows and some of the columns of X in such a way that each row of what is lef...
Stefano Lonardi, Wojciech Szpankowski, Qiaofeng Ya...
BMCBI
2010
110views more  BMCBI 2010»
13 years 5 months ago
Discovering local patterns of co - evolution: computational aspects and biological examples
Background: Co-evolution is the process in which two (or more) sets of orthologs exhibit a similar or correlative pattern of evolution. Co-evolution is a powerful way to learn abo...
Tamir Tuller, Yifat Felder, Martin Kupiec
BIBE
2004
IEEE
107views Bioinformatics» more  BIBE 2004»
13 years 9 months ago
Enhanced pClustering and Its Applications to Gene Expression Data
Clustering has been one of the most popular methods to discover useful biological insights from DNA microarray. An interesting paradigm is simultaneous clustering of both genes an...
Sungroh Yoon, Christine Nardini, Luca Benini, Giov...