SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms

BACKGROUND: The development of algorithms to infer the structure of gene regulatory networks based on expression data is an important subject in bioinformatics research. Validation of these algorithms requires benchmark data sets for which the underlying network is known. Since experimental data set...

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Détails bibliographiques
Auteurs principaux: Van den Bulcke, Tim, Van Leemput, Koenraad, Naudts, Bart, van Remortel, Piet, Ma, Hongwu, Verschoren, Alain, De Moor, Bart, Marchal, Kathleen
Format: Artigo
Langue:Inglês
Publié: BioMed Central 2006
Sujets:
Methodology Article
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC1373604/
https://ncbi.nlm.nih.gov/pubmed/16438721
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-7-43
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