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» A stable gene selection in microarray data analysis
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CSB
2005
IEEE
156views Bioinformatics» more  CSB 2005»
14 years 1 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,...
GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
14 years 1 months ago
A multi-objective approach to discover biclusters in microarray data
The main motivation for using a multi–objective evolutionary algorithm for finding biclusters in gene expression data is motivated by the fact that when looking for biclusters ...
Federico Divina, Jesús S. Aguilar-Ruiz
BMCBI
2008
159views more  BMCBI 2008»
13 years 7 months ago
Multivariate hierarchical Bayesian model for differential gene expression analysis in microarray experiments
Background: Identification of differentially expressed genes is a typical objective when analyzing gene expression data. Recently, Bayesian hierarchical models have become increas...
Hongya Zhao, Kwok-Leung Chan, Lee-Ming Cheng, Hong...
BMCBI
2008
102views more  BMCBI 2008»
13 years 7 months ago
Response projected clustering for direct association with physiological and clinical response data
Background: Microarray gene expression data are often analyzed together with corresponding physiological response and clinical metadata of biological subjects, e.g. patients'...
Sung-Gon Yi, Taesung Park, Jae K. Lee
COMPLIFE
2006
Springer
13 years 11 months ago
Relational Subgroup Discovery for Descriptive Analysis of Microarray Data
Abstract. This paper presents a method that uses gene ontologies, together with the paradigm of relational subgroup discovery, to help find description of groups of genes different...
Igor Trajkovski, Filip Zelezný, Jakub Tolar...