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» A cross-comparison of a large dataset of genes
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DSS
2007
127views more  DSS 2007»
13 years 7 months ago
Large-scale regulatory network analysis from microarray data: modified Bayesian network learning and association rule mining
We present two algorithms for learning large-scale gene regulatory networks from microarray data: a modified informationtheory-based Bayesian network algorithm and a modified asso...
Zan Huang, Jiexun Li, Hua Su, George S. Watts, Hsi...
BMCBI
2005
73views more  BMCBI 2005»
13 years 7 months ago
Evaluation of Glycine max mRNA clusters
Background: Clustering the ESTs from a large dataset representing a single species is a convenient starting point for a number of investigations into gene discovery, genome evolut...
Ronald L. Frank, Fikret Erçal
CSB
2005
IEEE
165views Bioinformatics» more  CSB 2005»
13 years 9 months ago
Sequential Diagonal Linear Discriminant Analysis (SeqDLDA) for Microarray Classification and Gene Identification
In microarray classification we are faced with a very large number of features and very few training samples. This is a challenge for classical Linear Discriminant Analysis (LDA),...
Roger Pique-Regi, Antonio Ortega, Shahab Asgharzad...
BIBE
2007
IEEE
136views Bioinformatics» more  BIBE 2007»
13 years 9 months ago
A Two-Stage Gene Selection Algorithm by Combining ReliefF and mRMR
Abstract—Gene expression data usually contains a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes ...
Yi Zhang, Chris H. Q. Ding, Tao Li
APBC
2003
128views Bioinformatics» more  APBC 2003»
13 years 9 months ago
Machine Learning in DNA Microarray Analysis for Cancer Classification
The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it e...
Sung-Bae Cho, Hong-Hee Won