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KES
2006
Springer
13 years 5 months ago
Combined Gene Selection Methods for Microarray Data Analysis
In recent years, the rapid development of DNA Microarray technology has made it possible for scientists to monitor the expression level of thousands of genes in a single experiment...
Hong Hu, Jiuyong Li, Hua Wang, Grant Daggard
SIGKDD
2002
113views more  SIGKDD 2002»
13 years 5 months ago
Combining Data and Text Mining Techniques for Yeast Gene Regulation Prediction: A Case Study
In order to solve task 2 of the KDD Cup 2002, we exploited various available information sources. In particular, use of relational information describing the interactions among ge...
Mark-A. Krogel, Marcus Denecke, Marco Landwehr, To...
BMCBI
2008
101views more  BMCBI 2008»
13 years 5 months ago
Reranking candidate gene models with cross-species comparison for improved gene prediction
Background: Most gene finders score candidate gene models with state-based methods, typically HMMs, by combining local properties (coding potential, splice donor and acceptor patt...
Qian Liu, Koby Crammer, Fernando C. N. Pereira, Da...
BMCBI
2007
143views more  BMCBI 2007»
13 years 5 months ago
Gene selection for classification of microarray data based on the Bayes error
Background: With DNA microarray data, selecting a compact subset of discriminative genes from thousands of genes is a critical step for accurate classification of phenotypes for, ...
Ji-Gang Zhang, Hong-Wen Deng
BMCBI
2010
196views more  BMCBI 2010»
13 years 3 months ago
Content-based microarray search using differential expression profiles
Background: With the expansion of public repositories such as the Gene Expression Omnibus (GEO), we are rapidly cataloging cellular transcriptional responses to diverse experiment...
Jesse M. Engreitz, Alexander A. Morgan, Joel Dudle...