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» Using Bayesian networks to analyze expression data
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GECCO
2003
Springer
191views Optimization» more  GECCO 2003»
15 years 3 months ago
Artificial Immune System for Classification of Gene Expression Data
DNA microarray experiments generate thousands of gene expression measurement simultaneously. Analyzing the difference of gene expression in cell and tissue samples is useful in dia...
Shin Ando, Hitoshi Iba
BMCBI
2010
96views more  BMCBI 2010»
14 years 10 months ago
A statistical framework for differential network analysis from microarray data
Background: It has been long well known that genes do not act alone; rather groups of genes act in consort during a biological process. Consequently, the expression levels of gene...
Ryan Gill, Somnath Datta, Susmita Datta
ICDM
2010
IEEE
147views Data Mining» more  ICDM 2010»
14 years 7 months ago
Subgroup Discovery Meets Bayesian Networks -- An Exceptional Model Mining Approach
Whenever a dataset has multiple discrete target variables, we want our algorithms to consider not only the variables themselves, but also the interdependencies between them. We pro...
Wouter Duivesteijn, Arno J. Knobbe, Ad Feelders, M...
ISBI
2004
IEEE
15 years 10 months ago
Microarray Gene Expression Data Analysis
Image analysis is a crucial step in processing microarray data generated by gene expression studies, which have been used extensively in understanding the molecular mechanisms of ...
Yuhua Ding, Jacqueline Fairley, George J. Vachtsev...
ICPR
2008
IEEE
15 years 11 months ago
Visual features with semantic combination using Bayesian network for a more effective image retrieval
In many vision problems, instead of having fully annotated training data, it is easier to obtain just a subset of data with annotations, because it is less restrictive for the use...
Sabine Barrat, Salvatore Tabbone