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» Gene Expression Clustering with Functional Mixture Models
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GECCO
2003
Springer
127views Optimization» more  GECCO 2003»
14 years 3 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 ...
BMCBI
2006
116views more  BMCBI 2006»
13 years 10 months ago
Optimized mixed Markov models for motif identification
Background: Identifying functional elements, such as transcriptional factor binding sites, is a fundamental step in reconstructing gene regulatory networks and remains a challengi...
Weichun Huang, David M. Umbach, Uwe Ohler, Leping ...
BMCBI
2007
145views more  BMCBI 2007»
13 years 10 months ago
Colony size measurement of the yeast gene deletion strains for functional genomics
Background: Numerous functional genomics approaches have been developed to study the model organism yeast, Saccharomyces cerevisiae, with the aim of systematically understanding t...
Negar Memarian, Matthew Jessulat, Javad Alirezaie,...
BMCBI
2008
121views more  BMCBI 2008»
13 years 10 months ago
Microarray data mining using landmark gene-guided clustering
Background: Clustering is a popular data exploration technique widely used in microarray data analysis. Most conventional clustering algorithms, however, generate only one set of ...
Pankaj Chopra, Jaewoo Kang, Jiong Yang, HyungJun C...
ICASSP
2010
IEEE
13 years 10 months ago
Swift: Scalable weighted iterative sampling for flow cytometry clustering
Flow cytometry (FC) is a powerful technology for rapid multivariate analysis and functional discrimination of cells. Current FC platforms generate large, high-dimensional datasets...
Iftekhar Naim, Suprakash Datta, Gaurav Sharma, Jam...