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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Bibliografiska uppgifter
Huvudupphovsmän: Van den Bulcke, Tim, Van Leemput, Koenraad, Naudts, Bart, van Remortel, Piet, Ma, Hongwu, Verschoren, Alain, De Moor, Bart, Marchal, Kathleen
Materialtyp: Artigo
Språk:Inglês
Publicerad: BioMed Central 2006
Ämnen:
Methodology Article
Länkar: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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