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BMCBI
2010
154views more  BMCBI 2010»
13 years 2 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
2007
135views more  BMCBI 2007»
13 years 2 months ago
Detecting multivariate differentially expressed genes
Background: Gene expression is governed by complex networks, and differences in expression patterns between distinct biological conditions may therefore be complex and multivariat...
Roland Nilsson, José M. Peña, Johan ...
BIBM
2009
IEEE
172views Bioinformatics» more  BIBM 2009»
13 years 8 months ago
Identifying Gene Signatures from Cancer Progression Data Using Ordinal Analysis
—A comprehensive understanding of cancer progression may shed light on genetic and molecular mechanisms of oncogenesis, and it may provide much needed information for effective d...
Yoon Soo Pyon, Jing Li
TSMC
2008
136views more  TSMC 2008»
13 years 2 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
2008
160views more  BMCBI 2008»
13 years 2 months ago
Predicting cancer involvement of genes from heterogeneous data
Background: Systematic approaches for identifying proteins involved in different types of cancer are needed. Experimental techniques such as microarrays are being used to characte...
Ramon Aragues, Chris Sander, Baldo Oliva