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BMCBI
2008
166views more  BMCBI 2008»
13 years 7 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
CIBCB
2007
IEEE
13 years 11 months ago
Associative Artificial Neural Network for Discovery of Highly Correlated Gene Groups Based on Gene Ontology and Gene Expression
Abstract-- The advance of high-throughput experimental technologies poses continuous challenges to computational data analysis in functional and comparative genomics studies. Gene ...
Ji He, Xinbin Dai, Xuechun Zhao
BMCBI
2010
172views more  BMCBI 2010»
13 years 7 months ago
Inferring gene regression networks with model trees
Background: Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to f...
Isabel A. Nepomuceno-Chamorro, Jesús S. Agu...
GPB
2010
231views Solid Modeling» more  GPB 2010»
13 years 4 months ago
Mining Gene Expression Profiles: An Integrated Implementation of Kernel Principal Component Analysis and Singular Value Decompos
The detection of genes that show similar profiles under different experimental conditions is often an initial step in inferring the biological significance of such genes. Visualiz...
Ferran Reverter, Esteban Vegas, Pedro Sánch...
BIOCOMP
2008
13 years 9 months ago
Reverse Engineering Module Networks by PSO-RNN Hybrid Modeling
Background: Inferring a gene regulatory network (GRN) from high throughput biological data is often an under-determined problem and is a challenging task due to the following reas...
Yuji Zhang, Jianhua Xuan, Benildo de los Reyes, Ro...