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» Evolutionary Biclustering of Microarray Data
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BIBE
2004
IEEE
107views Bioinformatics» more  BIBE 2004»
14 years 9 days ago
Enhanced pClustering and Its Applications to Gene Expression Data
Clustering has been one of the most popular methods to discover useful biological insights from DNA microarray. An interesting paradigm is simultaneous clustering of both genes an...
Sungroh Yoon, Christine Nardini, Luca Benini, Giov...
BMCBI
2006
119views more  BMCBI 2006»
13 years 8 months ago
LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates
Background: Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to iden...
Guoli Wang, Andrew V. Kossenkov, Michael F. Ochs
BMCBI
2010
172views more  BMCBI 2010»
13 years 8 months ago
Comparison of evolutionary algorithms in gene regulatory network model inference
Background: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineeri...
Alina Sîrbu, Heather J. Ruskin, Martin Crane
KES
2006
Springer
13 years 8 months ago
Evolutionary Tuning of Combined Multiple Models
Abstract. In data mining, hybrid intelligent systems present a synergistic combination of multiple approaches to develop the next generation of intelligent systems. Our paper prese...
Gregor Stiglic, Peter Kokol
GECCO
2003
Springer
127views Optimization» more  GECCO 2003»
14 years 1 months ago
Complex Function Sets Improve Symbolic Discriminant Analysis of Microarray Data
Abstract. Our ability to simultaneously measure the expression levels of thousands of genes in biological samples is providing important new opportunities for improving the diagnos...
David M. Reif, Bill C. White, Nancy Olsen, Thomas ...