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» Inferring Genetic Networks from Microarray Data
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BMCBI
2010
96views more  BMCBI 2010»
14 years 9 months ago
A statistical framework for differential network analysis from microarray data
Background: It has been long well known that genes do not act alone; rather groups of genes act in consort during a biological process. Consequently, the expression levels of gene...
Ryan Gill, Somnath Datta, Susmita Datta
BIOINFORMATICS
2002
146views more  BIOINFORMATICS 2002»
14 years 9 months ago
A duplication growth model of gene expression networks
Motivation: There has been considerable interest in developing computational techniques for inferring genetic regulatory networks from whole-genome expression profiles. When expre...
Ashish Bhan, David J. Galas, T. Gregory Dewey
BMCBI
2005
122views more  BMCBI 2005»
14 years 9 months ago
A microarray data-based semi-kinetic method for predicting quantitative dynamics of genetic networks
Background: Elucidating the dynamic behaviour of genetic regulatory networks is one of the most significant challenges in systems biology. However, conventional quantitative predi...
Katsuyuki Yugi, Yoichi Nakayama, Shigen Kojima, To...
CSB
2002
IEEE
169views Bioinformatics» more  CSB 2002»
15 years 2 months ago
Bayesian Network and Nonparametric Heteroscedastic Regression for Nonlinear Modeling of Genetic Network
We propose a new statistical method for constructing a genetic network from microarray gene expression data by using a Bayesian network. An essential point of Bayesian network con...
Seiya Imoto, SunYong Kim, Takao Goto, Sachiyo Abur...
BMCBI
2010
172views more  BMCBI 2010»
14 years 9 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