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» Inferring gene regression networks with model trees
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ECCB
2003
IEEE
13 years 11 months ago
Gene networks inference using dynamic Bayesian networks
This article deals with the identification of gene regulatory networks from experimental data using a statistical machine learning approach. A stochastic model of gene interactio...
Bruno-Edouard Perrin, Liva Ralaivola, Aurél...
ISMB
1993
13 years 7 months ago
Knowledge Discovery in GENBANK
Wedescribe various methods designed to discover knowledge in the GenBanknucleic acid sequence database. Using a grammatical model of gene structure, we create a parse tree of a ge...
Jeffery S. Aaronson, Juergen Haas, G. Christian Ov...
BMCBI
2011
12 years 9 months ago
A Simple Approach to Ranking Differentially Expressed Gene Expression Time Courses through Gaussian Process Regression
Background: The analysis of gene expression from time series underpins many biological studies. Two basic forms of analysis recur for data of this type: removing inactive (quiet) ...
Alfredo A. Kalaitzis, Neil D. Lawrence
BIOCOMP
2008
13 years 7 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...
BMCBI
2010
172views more  BMCBI 2010»
13 years 6 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