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» Combined Gene Selection Methods for Microarray Data Analysis
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112
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BMCBI
2010
118views more  BMCBI 2010»
15 years 2 months ago
Testing for mean and correlation changes in microarray experiments: an application for pathway analysis
Background: Microarray experiments examine the change in transcript levels of tens of thousands of genes simultaneously. To derive meaningful data, biologists investigate the resp...
Mayer Alvo, Zhongzhu Liu, Andrew Williams, Carole ...
150
Voted
BMCBI
2006
147views more  BMCBI 2006»
15 years 2 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
112
Voted
PSB
2004
15 years 4 months ago
Modeling Cellular Processes with Variational Bayesian Cooperative Vector Quantizer
Gene expression of a cell is controlled by sophisticated cellular processes. The capability of inferring the states of these cellular processes would provide insight into the mech...
Xinghua Lu, Milos Hauskrecht, Roger S. Day
139
Voted
BMCBI
2004
185views more  BMCBI 2004»
15 years 2 months ago
Linear fuzzy gene network models obtained from microarray data by exhaustive search
Background: Recent technological advances in high-throughput data collection allow for experimental study of increasingly complex systems on the scale of the whole cellular genome...
Bahrad A. Sokhansanj, J. Patrick Fitch, Judy N. Qu...
BMCBI
2007
120views more  BMCBI 2007»
15 years 2 months ago
Re-sampling strategy to improve the estimation of number of null hypotheses in FDR control under strong correlation structures
Background: When conducting multiple hypothesis tests, it is important to control the number of false positives, or the False Discovery Rate (FDR). However, there is a tradeoff be...
Xin Lu, David L. Perkins