Sciweavers

57 search results - page 2 / 12
» Semi-supervised discovery of differential genes
Sort
View
BMCBI
2006
154views more  BMCBI 2006»
13 years 5 months ago
An improved procedure for gene selection from microarray experiments using false discovery rate criterion
Background: A large number of genes usually show differential expressions in a microarray experiment with two types of tissues, and the p-values of a proper statistical test are o...
James J. Yang, Mark C. K. Yang
BMCBI
2008
126views more  BMCBI 2008»
13 years 5 months ago
GeneChaser: Identifying all biological and clinical conditions in which genes of interest are differentially expressed
Background: The amount of gene expression data in the public repositories, such as NCBI Gene Expression Omnibus (GEO) has grown exponentially, and provides a gold mine for bioinfo...
Rong Chen, Rohan Mallelwar, Ajit Thosar, Shivkumar...
BMCBI
2004
135views more  BMCBI 2004»
13 years 4 months ago
Determination of the differentially expressed genes in microarray experiments using local FDR
Background: Thousands of genes in a genomewide data set are tested against some null hypothesis, for detecting differentially expressed genes in microarray experiments. The expect...
Julie Aubert, Avner Bar-Hen, Jean-Jacques Daudin, ...
BMCBI
2004
124views more  BMCBI 2004»
13 years 4 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...
BMCBI
2008
99views more  BMCBI 2008»
13 years 5 months ago
Ranking analysis of F-statistics for microarray data
Background: Microarray technology provides an efficient means for globally exploring physiological processes governed by the coordinated expression of multiple genes. However, ide...
Yuan-De Tan, Myriam Fornage, Hongyan Xu