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KDD
2004
ACM
237views Data Mining» more  KDD 2004»
14 years 8 months ago
Bayesian Model-Averaging in Unsupervised Learning From Microarray Data
Unsupervised identification of patterns in microarray data has been a productive approach to uncovering relationships between genes and the biological process in which they are in...
Mario Medvedovic, Junhai Guo
BMCBI
2008
126views more  BMCBI 2008»
13 years 7 months ago
GeneChaser: Identifying all biological and clinical conditions in which genes of interest are differentially expressed
Background: The amount of gene expression data in the public repositories, such as NCBI Gene Expression Omnibus (GEO) has grown exponentially, and provides a gold mine for bioinfo...
Rong Chen, Rohan Mallelwar, Ajit Thosar, Shivkumar...
BMCBI
2006
146views more  BMCBI 2006»
13 years 7 months ago
Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE
Background: In class prediction problems using microarray data, gene selection is essential to improve the prediction accuracy and to identify potential marker genes for a disease...
Satoshi Niijima, Satoru Kuhara
KDD
2002
ACM
183views Data Mining» more  KDD 2002»
14 years 8 months ago
E-CAST: A Data Mining Algorithm for Gene Expression Data
Data clustering methods have been proven to be a successful data mining technique in the analysis of gene expression data. The Cluster affinity search technique (CAST) developed b...
Abdelghani Bellaachia, David Portnoy, Yidong Chen,...
BMCBI
2006
160views more  BMCBI 2006»
13 years 7 months ago
MIMAS: an innovative tool for network-based high density oligonucleotide microarray data management and annotation
Background: The high-density oligonucleotide microarray (GeneChip) is an important tool for molecular biological research aiming at large-scale detection of small nucleotide polym...
Leandro Hermida, Olivier Schaad, Philippe Demougin...