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CANDC
2005
ACM
13 years 7 months ago
Gene selection from microarray data for cancer classification - a machine learning approach
A DNA microarray can track the expression levels of thousands of genes simultaneously. Previous research has demonstrated that this technology can be useful in the classification ...
Yu Wang 0008, Igor V. Tetko, Mark A. Hall, Eibe Fr...
RECOMB
2009
Springer
14 years 8 months ago
Evaluating Between-Pathway Models with Expression Data
Abstract. Between-Pathway Models (BPMs) are network motifs consisting of pairs of putative redundant pathways. In this paper, we show how adding another source of high-throughput d...
Benjamin J. Hescott, Mark D. M. Leiserson, Lenore ...
BMCBI
2008
159views more  BMCBI 2008»
13 years 7 months ago
Multivariate hierarchical Bayesian model for differential gene expression analysis in microarray experiments
Background: Identification of differentially expressed genes is a typical objective when analyzing gene expression data. Recently, Bayesian hierarchical models have become increas...
Hongya Zhao, Kwok-Leung Chan, Lee-Ming Cheng, Hong...
BMCBI
2010
105views more  BMCBI 2010»
13 years 7 months ago
Evaluation of fecal mRNA reproducibility via a marginal transformed mixture modeling approach
Background: Developing and evaluating new technology that enables researchers to recover gene-expression levels of colonic cells from fecal samples could be key to a non-invasive ...
Nysia I. George, Joanne R. Lupton, Nancy D. Turner...
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...