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» Genes, Themes, and Microarrays: Using Information Retrieval ...
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BMCBI
2011
12 years 11 months ago
Gene set analysis for longitudinal gene expression data
Background: Gene set analysis (GSA) has become a successful tool to interpret gene expression profiles in terms of biological functions, molecular pathways, or genomic locations. ...
Ke Zhang, Haiyan Wang, Arne C. Bathke, Solomon W. ...
BMCBI
2006
147views more  BMCBI 2006»
13 years 7 months ago
Grouping Gene Ontology terms to improve the assessment of gene set enrichment in microarray data
Background: Gene Ontology (GO) terms are often used to assess the results of microarray experiments. The most common way to do this is to perform Fisher's exact tests to find...
Alex Lewin, Ian C. Grieve
BMCBI
2007
112views more  BMCBI 2007»
13 years 7 months ago
Selecting dissimilar genes for multi-class classification, an application in cancer subtyping
Background: Gene expression microarray is a powerful technology for genetic profiling diseases and their associated treatments. Such a process involves a key step of biomarker ide...
Zhipeng Cai, Randy Goebel, Mohammad R. Salavatipou...
JIFS
2002
134views more  JIFS 2002»
13 years 7 months ago
Classification of gene expression data using fuzzy logic
Microarray technologies have allowed the measurement of expression of multiple genes simultaneously. Gene expression levels can be used to classify tissues into diagnostic or progn...
Lucila Ohno-Machado, Staal A. Vinterbo, Griffin We...
BMCBI
2005
118views more  BMCBI 2005»
13 years 7 months ago
Feature selection and classification for microarray data analysis: Evolutionary methods for identifying predictive genes
Background: In the clinical context, samples assayed by microarray are often classified by cell line or tumour type and it is of interest to discover a set of genes that can be us...
Thanyaluk Jirapech-Umpai, J. Stuart Aitken