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» Probabilistic hierarchical clustering for biological data
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BMCBI
2006
155views more  BMCBI 2006»
13 years 8 months ago
Analysis of promoter regions of co-expressed genes identified by microarray analysis
Background: The use of global gene expression profiling to identify sets of genes with similar expression patterns is rapidly becoming a widespread approach for understanding biol...
Srinivas Veerla, Mattias Höglund
PSB
2003
13 years 9 months ago
Decomposing Gene Expression into Cellular Processes
We propose a probabilistic model for cellular processes, and an algorithm for discovering them from gene expression data. A process is associated with a set of genes that particip...
Eran Segal, Alexis Battle, Daphne Koller
RECOMB
2002
Springer
14 years 8 months ago
Discovering local structure in gene expression data: the order-preserving submatrix problem
This paper concerns the discovery of patterns in gene expression matrices, in which each element gives the expression level of a given gene in a given experiment. Most existing me...
Amir Ben-Dor, Benny Chor, Richard M. Karp, Zohar Y...
GECCO
2005
Springer
156views Optimization» more  GECCO 2005»
14 years 1 months ago
Extraction of informative genes from microarray data
Identification of those genes that might anticipate the clinical behavior of different types of cancers is challenging due to availability of a smaller number of patient samples...
Topon Kumar Paul, Hitoshi Iba
ICDE
2003
IEEE
247views Database» more  ICDE 2003»
14 years 9 months ago
CLUSEQ: Efficient and Effective Sequence Clustering
Analyzing sequence data has become increasingly important recently in the area of biological sequences, text documents, web access logs, etc. In this paper, we investigate the pro...
Jiong Yang, Wei Wang 0010