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BMCBI
2006
239views more  BMCBI 2006»
14 years 9 months ago
Applying dynamic Bayesian networks to perturbed gene expression data
Background: A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics,...
Norbert Dojer, Anna Gambin, Andrzej Mizera, Bartek...
BMCBI
2010
143views more  BMCBI 2010»
14 years 9 months ago
Learning gene regulatory networks from only positive and unlabeled data
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
Luigi Cerulo, Charles Elkan, Michele Ceccarelli
GECCO
2006
Springer
220views Optimization» more  GECCO 2006»
15 years 1 months ago
Comparing evolutionary algorithms on the problem of network inference
In this paper, we address the problem of finding gene regulatory networks from experimental DNA microarray data. We focus on the evaluation of the performance of different evoluti...
Christian Spieth, Rene Worzischek, Felix Streicher...
JCP
2006
157views more  JCP 2006»
14 years 9 months ago
CF-GeNe: Fuzzy Framework for Robust Gene Regulatory Network Inference
Most Gene Regulatory Network (GRN) studies ignore the impact of the noisy nature of gene expression data despite its significant influence upon inferred results. This paper present...
Muhammad Shoaib B. Sehgal, Iqbal Gondal, Laurence ...
ECCB
2008
IEEE
15 years 3 months ago
SIRENE: supervised inference of regulatory networks
Living cells are the product of gene expression programs that involve the regulated transcription of thousands of genes. The elucidation of transcriptional regulatory networks in ...
Fantine Mordelet, Jean-Philippe Vert