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» Microarray Gene Expression Data Analysis
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CIBCB
2005
IEEE
15 years 3 months ago
Feature Selection for Microarray Data Using Least Squares SVM and Particle Swarm Optimization
Feature selection is an important preprocessing technique for many pattern recognition problems. When the number of features is very large while the number of samples is relatively...
E. Ke Tang, Ponnuthurai N. Suganthan, Xin Yao
BMCBI
2004
117views more  BMCBI 2004»
14 years 9 months ago
Cancer characterization and feature set extraction by discriminative margin clustering
Background: A central challenge in the molecular diagnosis and treatment of cancer is to define a set of molecular features that, taken together, distinguish a given cancer, or ty...
Kamesh Munagala, Robert Tibshirani, Patrick O. Bro...
BMCBI
2006
108views more  BMCBI 2006»
14 years 9 months ago
Probe set algorithms: is there a rational best bet?
Affymetrix microarrays have become a standard experimental platform for studies of mRNA expression profiling. Their success is due, in part, to the multiple oligonucleotide featur...
Jinwook Seo, Eric P. Hoffman
RECOMB
2004
Springer
15 years 10 months ago
Predicting Genetic Regulatory Response Using Classification: Yeast Stress Response
We present a novel classification-based algorithm called GeneClass for learning to predict gene regulatory response. Our approach is motivated by the hypothesis that in simple orga...
Manuel Middendorf, Anshul Kundaje, Chris Wiggins, ...
ICCSA
2005
Springer
15 years 3 months ago
A Penalized Likelihood Estimation on Transcriptional Module-Based Clustering
In this paper, we propose a new clustering procedure for high dimensional microarray data. Major difficulty in cluster analysis of microarray data is that the number of samples to ...
Ryo Yoshida, Seiya Imoto, Tomoyuki Higuchi