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» Tissue classification with gene expression profiles
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GECCO
2007
Springer
179views Optimization» more  GECCO 2007»
15 years 5 months ago
Evolutionary selection of minimum number of features for classification of gene expression data using genetic algorithms
Selecting the most relevant factors from genetic profiles that can optimally characterize cellular states is of crucial importance in identifying complex disease genes and biomark...
Alper Küçükural, Reyyan Yeniterzi...
NAR
2008
113views more  NAR 2008»
14 years 11 months ago
miRNAMap 2.0: genomic maps of microRNAs in metazoan genomes
MicroRNAs (miRNAs) are small non-coding RNA molecules that can negatively regulate gene expression and thus control numerous cellular mechanisms. This work develops a resource, mi...
Sheng-Da Hsu, Chia-Huei Chu, Ann-Ping Tsou, Shu-Je...
BIOINFORMATICS
2007
195views more  BIOINFORMATICS 2007»
14 years 11 months ago
Context-dependent clustering for dynamic cellular state modeling of microarray gene expression
Motivation: High-throughput expression profiling allows researchers to study gene activities globally. Genes with similar expression profiles are likely to encode proteins that ma...
Shinsheng Yuan, Ker-Chau Li
BMCBI
2006
129views more  BMCBI 2006»
14 years 11 months ago
Identifying genes that contribute most to good classification in microarrays
Background: The goal of most microarray studies is either the identification of genes that are most differentially expressed or the creation of a good classification rule. The dis...
Stuart G. Baker, Barnett S. Kramer
NIPS
2008
15 years 1 months ago
A mixture model for the evolution of gene expression in non-homogeneous datasets
We address the challenge of assessing conservation of gene expression in complex, non-homogeneous datasets. Recent studies have demonstrated the success of probabilistic models in...
Gerald Quon, Yee Whye Teh, Esther Chan, Timothy R....