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BMCBI
2004
205views more  BMCBI 2004»
15 years 4 months ago
A combinational feature selection and ensemble neural network method for classification of gene expression data
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Bing Liu, Qinghua Cui, Tianzi Jiang, Songde Ma
BMCBI
2010
193views more  BMCBI 2010»
14 years 11 months ago
Mayday - integrative analytics for expression data
Background: DNA Microarrays have become the standard method for large scale analyses of gene expression and epigenomics. The increasing complexity and inherent noisiness of the ge...
Florian Battke, Stephan Symons, Kay Nieselt
CEC
2003
IEEE
15 years 8 months ago
Dynamics of gene expression in an artificial genome
Abstract- Complex systems techniques provide a powerful tool to study the emergent properties of networks of interacting genes. In this study we extract models of genetic regulator...
Kai Willadsen, Janet Wiles
BMCBI
2008
111views more  BMCBI 2008»
15 years 4 months ago
Comparative optimism in models involving both classical clinical and gene expression information
Background: In cancer research, most clinical variables have already been investigated and are now well established. The use of transcriptomic variables has raised two problems: r...
Caroline Truntzer, Delphine Maucort-Boulch, Pascal...
BMCBI
2011
14 years 11 months ago
A theoretical entropy score as a single value to express inhibitor selectivity
Background: Designing maximally selective ligands that act on individual targets is the dominant paradigm in drug discovery. Poor selectivity can underlie toxicity and side effect...
Joost C. M. Uitdehaag, Guido J. R. Zaman