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An ensemble learning approach to reverse-engineering transcriptional regulatory networks from time-series gene expression data
BACKGROUND: One of the most challenging tasks in the post-genomic era is to reconstruct the transcriptional regulatory networks. The goal is to reveal, for each gene that responds to a certain biological event, which transcription factors affect its expression, and how a set of transcription factors...
| Autores principales: | , , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2009
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2709269/ https://www.ncbi.nlm.nih.gov/pubmed/19594885 http://dx.doi.org/10.1186/1471-2164-10-S1-S8 |