A probabilistic dynamical model for quantitative inference of the regulatory mechanism of transcription | Zendy

Guido Sanguinetti | Zendy; Magnus Rattray | Zendy; Neil D. Lawrence | Zendy

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A probabilistic dynamical model for quantitative inference of the regulatory mechanism of transcription

Author(s) -

Guido Sanguinetti,

Magnus Rattray,

Neil D. Lawrence

Publication year - 2006

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btl154

Subject(s) - computer science , computational biology , transcription factor , probabilistic logic , inference , gene regulatory network , statistical model , transcription (linguistics) , biology , gene , data mining , machine learning , gene expression , artificial intelligence , genetics , linguistics , philosophy

Quantitative estimation of the regulatory relationship between transcription factors and genes is a fundamental stepping stone when trying to develop models of cellular processes. This task, however, is difficult for a number of reasons: transcription factors' expression levels are often low and noisy, and many transcription factors are post-transcriptionally regulated. It is therefore useful to infer the activity of the transcription factors from the expression levels of their target genes.

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