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» Functional dissipation microarrays for classification
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NIPS
2004
15 years 1 months ago
PAC-Bayes Learning of Conjunctions and Classification of Gene-Expression Data
We propose a "soft greedy" learning algorithm for building small conjunctions of simple threshold functions, called rays, defined on single real-valued attributes. We al...
Mario Marchand, Mohak Shah
BMCBI
2008
179views more  BMCBI 2008»
14 years 11 months ago
Building pathway clusters from Random Forests classification using class votes
Background: Recent years have seen the development of various pathway-based methods for the analysis of microarray gene expression data. These approaches have the potential to bri...
Herbert Pang, Hongyu Zhao
BMCBI
2008
167views more  BMCBI 2008»
14 years 11 months ago
Expression profiles of switch-like genes accurately classify tissue and infectious disease phenotypes in model-based classificat
Background: Large-scale compilation of gene expression microarray datasets across diverse biological phenotypes provided a means of gathering a priori knowledge in the form of ide...
Michael Gormley, Aydin Tozeren
BMCBI
2005
121views more  BMCBI 2005»
14 years 11 months ago
Evaluation of gene importance in microarray data based upon probability of selection
Background: Microarray devices permit a genome-scale evaluation of gene function. This technology has catalyzed biomedical research and development in recent years. As many import...
Li M. Fu, Casey S. Fu-Liu
BMCBI
2006
126views more  BMCBI 2006»
14 years 11 months ago
Differential prioritization between relevance and redundancy in correlation-based feature selection techniques for multiclass ge
Background: Due to the large number of genes in a typical microarray dataset, feature selection looks set to play an important role in reducing noise and computational cost in gen...
Chia Huey Ooi, Madhu Chetty, Shyh Wei Teng