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» CoXpress: differential co-expression in gene expression data
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BMCBI
2006
155views more  BMCBI 2006»
13 years 8 months ago
A powerful method for detecting differentially expressed genes from GeneChip arrays that does not require replicates
Background: Studies of differential expression that use Affymetrix GeneChip arrays are often carried out with a limited number of replicates. Reasons for this include financial co...
Anne-Mette K. Hein, Sylvia Richardson
TSMC
2008
136views more  TSMC 2008»
13 years 8 months ago
Learning Relational Descriptions of Differentially Expressed Gene Groups
Abstract-- This paper presents a method that uses gene ontologies, together with the paradigm of relational subgroup discovery, to find compactly described groups of genes differen...
Igor Trajkovski, Filip Zelezný, Nada Lavrac...
BMCBI
2010
154views more  BMCBI 2010»
13 years 8 months ago
Candidate gene prioritization by network analysis of differential expression using machine learning approaches
Background: Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available...
Daniela Nitsch, Joana P. Gonçalves, Fabian ...
BMCBI
2004
169views more  BMCBI 2004»
13 years 8 months ago
A power law global error model for the identification of differentially expressed genes in microarray data
Background: High-density oligonucleotide microarray technology enables the discovery of genes that are transcriptionally modulated in different biological samples due to physiolog...
Norman Pavelka, Mattia Pelizzola, Caterina Vizzard...
BMCBI
2004
158views more  BMCBI 2004»
13 years 8 months ago
A novel Mixture Model Method for identification of differentially expressed genes from DNA microarray data
Background: The main goal in analyzing microarray data is to determine the genes that are differentially expressed across two types of tissue samples or samples obtained under two...
Kayvan Najarian, Maryam Zaheri, Ali Ajdari Rad, Si...