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» Improving gene set analysis of microarray data by SAM-GS
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BMEI
2009
IEEE
13 years 8 months ago
An Improved Probabilistic Model for Finding Differential Gene Expression
Abstract--Finding differentially expressed genes is a fundamental objective of a microarray experiment. Recently proposed method, PPLR, considers the probe-level measurement error ...
Li Zhang, Xuejun Liu
BMCBI
2004
126views more  BMCBI 2004»
13 years 7 months ago
Visualization and analysis of microarray and gene ontology data with treemaps
Background: The increasing complexity of genomic data presents several challenges for biologists. Limited computer monitor views of data complexity and the dynamic nature of data ...
Eric H. Baehrecke, Niem Dang, Ketan Babaria, Ben S...
BMCBI
2007
148views more  BMCBI 2007»
13 years 7 months ago
Computation of significance scores of unweighted Gene Set Enrichment Analyses
Background: Gene Set Enrichment Analysis (GSEA) is a computational method for the statistical evaluation of sorted lists of genes or proteins. Originally GSEA was developed for in...
Andreas Keller, Christina Backes, Hans-Peter Lenho...
BMCBI
2005
163views more  BMCBI 2005»
13 years 7 months ago
Rank-invariant resampling based estimation of false discovery rate for analysis of small sample microarray data
Background: The evaluation of statistical significance has become a critical process in identifying differentially expressed genes in microarray studies. Classical p-value adjustm...
Nitin Jain, HyungJun Cho, Michael O'Connell, Jae K...
BMCBI
2005
152views more  BMCBI 2005»
13 years 7 months ago
CoPub Mapper: mining MEDLINE based on search term co-publication
Background: High throughput microarray analyses result in many differentially expressed genes that are potentially responsible for the biological process of interest. In order to ...
Blaise T. F. Alako, Antoine Veldhoven, Sjozef van ...