Inferring gene regulatory networks by ANOVA

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چکیده

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Inferring gene regulatory networks by ANOVA

MOTIVATION To improve the understanding of molecular regulation events, various approaches have been developed for deducing gene regulatory networks from mRNA expression data. RESULTS We present a new score for network inference, η(2), that is derived from an analysis of variance. Candidate transcription factor:target gene (TF:TG) relationships are assumed more likely if the expression of TF ...

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Inferring Gene Regulatory Networks by Incremental Evolution and Network Decomposition

Constructing genetic regulatory networks from expression data is one of the most important issues in systems biology research. However, building regulatory models manually is a tedious task, especially when the number of genes involved increases with the complexity of regulation. To automate the procedure of network construction, we develop a methodology to infer S-systems as regulatory systems...

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Inferring Gene Regulatory Networks by Machine Learning Methods

The ability to measure the transcriptional response after a stimulus has drawn much attention to the underlying gene regulatory networks. Several machine learning related methods, such as Bayesian networks and decision trees, have been proposed to deal with this difficult problem, but rarely a systematic comparison between different algorithms has been performed. In this work, we critically eva...

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Inferring regulatory networks.

The discovery of regulatory networks is an important aspect in the post genomic research. The process requires integrated efforts of experimental and computational strategies by employing the systems biology approach. This review summarizes some of the major themes in computational inference of regulatory networks based on gene expression and other data sources, including transcriptional module...

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ژورنال

عنوان ژورنال: Bioinformatics

سال: 2012

ISSN: 1460-2059,1367-4803

DOI: 10.1093/bioinformatics/bts143