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CBMS
2005
IEEE
14 years 1 months ago
An Ontology-Driven Clustering Method for Supporting Gene Expression Analysis
The Gene Ontology (GO) is an important knowledge resource for biologists and bioinformaticians. This paper explores the integration of similarity information derived from GO into ...
Haiying Wang, Francisco Azuaje, Olivier Bodenreide...
BMCBI
2007
134views more  BMCBI 2007»
13 years 7 months ago
Nearest Neighbor Networks: clustering expression data based on gene neighborhoods
Background: The availability of microarrays measuring thousands of genes simultaneously across hundreds of biological conditions represents an opportunity to understand both indiv...
Curtis Huttenhower, Avi I. Flamholz, Jessica N. La...
BMCBI
2002
147views more  BMCBI 2002»
13 years 7 months ago
Expression profiling of human renal carcinomas with functional taxonomic analysis
Background: Molecular characterization has contributed to the understanding of the inception, progression, treatment and prognosis of cancer. Nucleic acid array-based technologies...
Michael A. Gieseg, Theresa Cody, Michael Z. Man, S...
BMCBI
2006
102views more  BMCBI 2006»
13 years 7 months ago
Microarray analysis distinguishes differential gene expression patterns from large and small colony Thymidine kinase mutants of
Background: The Thymidine kinase (Tk) mutants generated from the widely used L5178Y mouse lymphoma assay fall into two categories, small colony and large colony. Cells from the la...
Tao Han, Jianyong Wang, Weida Tong, Martha M. Moor...
CSDA
2008
128views more  CSDA 2008»
13 years 7 months ago
Assessing agreement of clustering methods with gene expression microarray data
In the rapidly evolving field of genomics, many clustering and classification methods have been developed and employed to explore patterns in gene expression data. Biologists face...
Xueli Liu, Sheng-Chien Lee, George Casella, Gary F...