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CSDA
2008
128views more  CSDA 2008»
13 years 7 months ago
Assessing agreement of clustering methods with gene expression microarray data
In the rapidly evolving field of genomics, many clustering and classification methods have been developed and employed to explore patterns in gene expression data. Biologists face...
Xueli Liu, Sheng-Chien Lee, George Casella, Gary F...
BMCBI
2004
124views more  BMCBI 2004»
13 years 7 months ago
Tests for finding complex patterns of differential expression in cancers: towards individualized medicine
Background: Microarray studies in cancer compare expression levels between two or more sample groups on thousands of genes. Data analysis follows a population-level approach (e.g....
James Lyons-Weiler, Satish Patel, Michael J. Becic...
ICASSP
2009
IEEE
14 years 2 months ago
Robust cross-race gene expression analysis
This paper develops a Bayesian network (BN) predictor to profile cross-race gene expression data. Cross-race studies face more data variability than single-lab studies. Our desig...
Hsun-Hsien Chang, Marco Ramoni
BMCBI
2008
88views more  BMCBI 2008»
13 years 7 months ago
Microarray-based gene set analysis: a comparison of current methods
Background: The analysis of gene sets has become a popular topic in recent times, with researchers attempting to improve the interpretability and reproducibility of their microarr...
Sarah Song, Michael A. Black
BMCBI
2006
156views more  BMCBI 2006»
13 years 7 months ago
GOFFA: Gene Ontology For Functional Analysis - A FDA Gene Ontology Tool for Analysis of Genomic and Proteomic Data
Background: Gene Ontology (GO) characterizes and categorizes the functions of genes and their products according to biological processes, molecular functions and cellular componen...
Hongmei Sun, Hong Fang, Tao Chen, Roger Perkins, W...