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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Detalles Bibliográficos
Autores principales: Van den Bulcke, Tim, Van Leemput, Koenraad, Naudts, Bart, van Remortel, Piet, Ma, Hongwu, Verschoren, Alain, De Moor, Bart, Marchal, Kathleen
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1373604/
https://www.ncbi.nlm.nih.gov/pubmed/16438721
http://dx.doi.org/10.1186/1471-2105-7-43

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1373604/
https://www.ncbi.nlm.nih.gov/pubmed/16438721
http://dx.doi.org/10.1186/1471-2105-7-43

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