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» Comparative analysis of biclustering algorithms
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BMCBI
2007
182views more  BMCBI 2007»
13 years 7 months ago
EDISA: extracting biclusters from multiple time-series of gene expression profiles
Background: Cells dynamically adapt their gene expression patterns in response to various stimuli. This response is orchestrated into a number of gene expression modules consistin...
Jochen Supper, Martin Strauch, Dierk Wanke, Klaus ...
CSB
2004
IEEE
173views Bioinformatics» more  CSB 2004»
13 years 11 months ago
Gene Ontology Friendly Biclustering of Expression Profiles
The soundness of clustering in the analysis of gene expression profiles and gene function prediction is based on the hypothesis that genes with similar expression profiles may imp...
Jinze Liu, Wei Wang 0010, Jiong Yang
BMCBI
2006
170views more  BMCBI 2006»
13 years 7 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...
PODS
2008
ACM
153views Database» more  PODS 2008»
14 years 7 months ago
Approximation algorithms for co-clustering
Co-clustering is the simultaneous partitioning of the rows and columns of a matrix such that the blocks induced by the row/column partitions are good clusters. Motivated by severa...
Aris Anagnostopoulos, Anirban Dasgupta, Ravi Kumar
EVOW
2005
Springer
14 years 1 months ago
Order Preserving Clustering over Multiple Time Course Experiments
Abstract. Clustering still represents the most commonly used technique to analyze gene expression data—be it classical clustering approaches that aim at finding biologically rel...
Stefan Bleuler, Eckart Zitzler