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» Gene set analysis for longitudinal gene expression data
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BMCBI
2010
144views more  BMCBI 2010»
13 years 7 months ago
Identifying overrepresented concepts in gene lists from literature: a statistical approach based on Poisson mixture model
Background: Large-scale genomic studies often identify large gene lists, for example, the genes sharing the same expression patterns. The interpretation of these gene lists is gen...
Xin He, Moushumi Sen Sarma, Xu Ling, Brant W. Chee...
RECOMB
2003
Springer
14 years 8 months ago
Joint classifier and feature optimization for cancer diagnosis using gene expression data
Recent research has demonstrated quite convincingly that accurate cancer diagnosis can be achieved by constructing classifiers that are designed to compare the gene expression pro...
Balaji Krishnapuram, Lawrence Carin, Alexander J. ...
APBC
2004
132views Bioinformatics» more  APBC 2004»
13 years 9 months ago
A Novel Feature Selection Method to Improve Classification of Gene Expression Data
This paper introduces a novel method for minimum number of gene (feature) selection for a classification problem based on gene expression data with an objective function to maximi...
Liang Goh, Qun Song, Nikola K. Kasabov
CSB
2005
IEEE
143views Bioinformatics» more  CSB 2005»
14 years 1 months ago
Multivariate gene selection: Does it help
When building predictors of disease state based on gene expression data, gene selection is performed in order to achieve a good performance and to identify a relevant subset of ge...
Carmen Lai, Marcel J. T. Reinders
BMCBI
2007
106views more  BMCBI 2007»
13 years 7 months ago
Modeling SAGE tag formation and its effects on data interpretation within a Bayesian framework
Background: Serial Analysis of Gene Expression (SAGE) is a high-throughput method for inferring mRNA expression levels from the experimentally generated sequence based tags. Stand...
Michael A. Gilchrist, Hong Qin, Russell L. Zaretzk...