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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...
| Autores principales: | , , , , , , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2006
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| Materias: | |
| 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 |