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BMCBI
2004
146views more  BMCBI 2004»
13 years 8 months ago
Defining transcriptional networks through integrative modeling of mRNA expression and transcription factor binding data
Background: Functional genomics studies are yielding information about regulatory processes in the cell at an unprecedented scale. In the yeast S. cerevisiae, DNA microarrays have...
Feng Gao, Barrett C. Foat, Harmen J. Bussemaker
ICMLA
2008
13 years 10 months ago
Microarray Classification from Several Two-Gene Expression Comparisons
We describe our contribution to the ICMLA2008 "Automated Micro-Array Classification Challenge". The design of our classifier is motivated by the special scenario encounte...
Donald Geman, Bahman Afsari, Aik Choon Tan, Daniel...
BMCBI
2008
160views more  BMCBI 2008»
13 years 8 months ago
A comparison of four clustering methods for brain expression microarray data
Background: DNA microarrays, which determine the expression levels of tens of thousands of genes from a sample, are an important research tool. However, the volume of data they pr...
Alexander L. Richards, Peter Holmans, Michael C. O...
RECOMB
2000
Springer
14 years 5 days ago
Using Bayesian networks to analyze expression data
DNA hybridization arrays simultaneously measure the expression level for thousands of genes. These measurements provide a "snapshot" of transcription levels within the c...
Nir Friedman, Michal Linial, Iftach Nachman, Dana ...
GECCO
2000
Springer
123views Optimization» more  GECCO 2000»
14 years 6 days ago
Genomic computing: explanatory modelling for functional genomics
Many newly discovered genes are of unknown function. DNA microarrays are a method for determining the expression levels of all genes in an organism for which a complete genome seq...
Richard J. Gilbert, Jem J. Rowland, Douglas B. Kel...