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» Gene Classification using Expression Profiles: A Feasibility...
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BMCBI
2008
167views more  BMCBI 2008»
13 years 5 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
AUSAI
2007
Springer
13 years 9 months ago
Hybrid Methods to Select Informative Gene Sets in Microarray Data Classification
Abstract. One of the key applications of microarray studies is to select and classify gene expression profiles of cancer and normal subjects. In this study, two hybrid approaches
Pengyi Yang, Zili Zhang
SAC
2008
ACM
13 years 3 months ago
Strangeness-based feature weighting and classification of gene expression profiles
Achieving high classification accuracy is a major challenge in the diagnosis of cancer types based on gene expression profiles. These profiles are notoriously noisy in that a larg...
Haifeng Shao, Bei Yu, Joseph H. Nadeau
BMCBI
2005
190views more  BMCBI 2005»
13 years 5 months ago
An Entropy-based gene selection method for cancer classification using microarray data
Background: Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of n...
Xiaoxing Liu, Arun Krishnan, Adrian Mondry
BMCBI
2004
150views more  BMCBI 2004»
13 years 5 months ago
Rank Difference Analysis of Microarrays (RDAM), a novel approach to statistical analysis of microarray expression profiling data
Background: A key step in the analysis of microarray expression profiling data is the identification of genes that display statistically significant changes in expression signals ...
Dietmar E. Martin, Philippe Demougin, Michael N. H...