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BMCBI
2007
143views more  BMCBI 2007»
13 years 5 months ago
Gene selection for classification of microarray data based on the Bayes error
Background: With DNA microarray data, selecting a compact subset of discriminative genes from thousands of genes is a critical step for accurate classification of phenotypes for, ...
Ji-Gang Zhang, Hong-Wen Deng
BIOCOMP
2007
13 years 6 months ago
Biomarker Discovery Across Annotated and Unannotated Microarray Datasets Using Semi-Supervised Learning
The growing body of DNA microarray data has the potential to advance our understanding of the molecular basis of disease. However annotating microarray datasets with clinically us...
Cole Harris, Noushin Ghaffari
JMLR
2010
125views more  JMLR 2010»
13 years 3 days ago
On utility of gene set signatures in gene expression-based cancer class prediction
Machine learning methods that can use additional knowledge in their inference process are central to the development of integrative bioinformatics. Inclusion of background knowled...
Minca Mramor, Marko Toplak, Gregor Leban, Tomaz Cu...
BMCBI
2005
151views more  BMCBI 2005»
13 years 5 months ago
stam - a Bioconductor compliant R package for structured analysis of microarray data
Background: Genome wide microarray studies have the potential to unveil novel disease entities. Clinically homogeneous groups of patients can have diverse gene expression profiles...
Claudio Lottaz, Rainer Spang
BMCBI
2006
91views more  BMCBI 2006»
13 years 5 months ago
Empirical study of supervised gene screening
Background: Microarray studies provide a way of linking variations of phenotypes with their genetic causations. Constructing predictive models using high dimensional microarray me...
Shuangge Ma