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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...

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Библиографические подробности
Главные авторы: Ruan, Jianhua, Deng, Youping, Perkins, Edward J, Zhang, Weixiong
Формат: Artigo
Язык:Inglês
Опубликовано: BioMed Central 2009
Предметы:
Online-ссылка:https://ncbi.nlm.nih.gov/pmc/articles/PMC2709269/
https://ncbi.nlm.nih.gov/pubmed/19594885
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2164-10-S1-S8
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