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IEAAIE
2010
Springer
13 years 3 months ago
Constructive Neural Networks to Predict Breast Cancer Outcome by Using Gene Expression Profiles
Abstract. Gene expression profiling strategies have attracted considerable interest from biologist due to the potential for high throughput analysis of hundreds of thousands of gen...
Daniel Urda, José Luis Subirats, Leonardo F...
BMCBI
2006
129views more  BMCBI 2006»
13 years 5 months ago
Identifying genes that contribute most to good classification in microarrays
Background: The goal of most microarray studies is either the identification of genes that are most differentially expressed or the creation of a good classification rule. The dis...
Stuart G. Baker, Barnett S. Kramer
ICMLA
2008
13 years 7 months ago
Microarray Classification from Several Two-Gene Expression Comparisons
We describe our contribution to the ICMLA2008 "Automated Micro-Array Classification Challenge". The design of our classifier is motivated by the special scenario encounte...
Donald Geman, Bahman Afsari, Aik Choon Tan, Daniel...
BMCBI
2007
140views more  BMCBI 2007»
13 years 5 months ago
Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets
Background: Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles...
Michael Gormley, William Dampier, Adam Ertel, Bilg...
CSB
2005
IEEE
156views Bioinformatics» more  CSB 2005»
13 years 11 months ago
A Robust Meta-classification Strategy for Cancer Diagnosis from Gene Expression Data
One of the major challenges in cancer diagnosis from microarray data is to develop robust classification models which are independent of the analysis techniques used and can combi...
Gabriela Alexe, Gyan Bhanot, Babu Venkataraghavan,...