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» Using Bayesian networks to analyze expression data
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CSB
2003
IEEE
153views Bioinformatics» more  CSB 2003»
13 years 10 months ago
Combining Microarrays and Biological Knowledge for Estimating Gene Networks via Bayesian Networks
We propose a statistical method for estimating a gene network based on Bayesian networks from microarray gene expression data together with biological knowledge including protein-...
Seiya Imoto, Tomoyuki Higuchi, Takao Goto, Kousuke...
BMCBI
2008
166views more  BMCBI 2008»
13 years 5 months ago
Learning transcriptional regulatory networks from high throughput gene expression data using continuous three-way mutual informa
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
Weijun Luo, Kurt D. Hankenson, Peter J. Woolf
WILF
2005
Springer
194views Fuzzy Logic» more  WILF 2005»
13 years 10 months ago
Learning Bayesian Classifiers from Gene-Expression MicroArray Data
Computing methods that allow the efficient and accurate processing of experimentally gathered data play a crucial role in biological research. The aim of this paper is to present a...
Andrea Bosin, Nicoletta Dessì, Diego Libera...
BMCBI
2008
201views more  BMCBI 2008»
13 years 5 months ago
A copula method for modeling directional dependence of genes
Background: Genes interact with each other as basic building blocks of life, forming a complicated network. The relationship between groups of genes with different functions can b...
Jong-Min Kim, Yoon-Sung Jung, Engin A. Sungur, Kap...
BIBE
2006
IEEE
139views Bioinformatics» more  BIBE 2006»
13 years 11 months ago
A Computational Inference Framework for analyzing Gene Regulation Pathway using Microarray Data
Microarray experiments produce gene expression data at such a high speed and volume that it is imperative to use highly specialized computational tools for their analyses. One grou...
Dong-Guk Shin, John Bluis, Yoo Ah Kim, Winfried Kr...