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» Combined Gene Selection Methods for Microarray Data Analysis
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BMCBI
2010
153views more  BMCBI 2010»
15 years 3 months ago
GOAL: A software tool for assessing biological significance of genes groups
Background: Modern high throughput experimental techniques such as DNA microarrays often result in large lists of genes. Computational biology tools such as clustering are then us...
Alain B. Tchagang, Alexander Gawronski, Hugo B&eac...
ICPR
2006
IEEE
16 years 4 months ago
Finding Rule Groups to Classify High Dimensional Gene Expression Datasets
Microarray data provides quantitative information about the transcription profile of cells. To analyze microarray datasets, methodology of machine learning has increasingly attrac...
Jiyuan An, Yi-Ping Phoebe Chen
BIOINFORMATICS
2005
72views more  BIOINFORMATICS 2005»
15 years 2 months ago
Use of within-array replicate spots for assessing differential expression in microarray experiments
Motivation. Spotted arrays are often printed with probes in duplicate or triplicate, but current methods for assessing differential expression are not able to make full use of the...
Gordon K. Smyth, Joëlle Michaud, Hamish S. Sc...
BMCBI
2004
100views more  BMCBI 2004»
15 years 2 months ago
Handling multiple testing while interpreting microarrays with the Gene Ontology Database
Background: The development of software tools that analyze microarray data in the context of genetic knowledgebases is being pursued by multiple research groups using different me...
Michael V. Osier, Hongyu Zhao, Kei-Hoi Cheung
BMCBI
2008
128views more  BMCBI 2008»
15 years 3 months ago
Validation of an NSP-based (negative selection pattern) gene family identification strategy
Background: Gene family identification from ESTs can be a valuable resource for analysis of genome evolution but presents unique challenges in organisms for which the entire genom...
Ronald L. Frank, Cyriac Kandoth, Fikret Erç...