Learning gene network structure from time laps cell imaging in RNAi Knock downs | Zendy

Henrik Failmezger | Zendy; Paurush Praveen | Zendy; Achim Tresch | Zendy; Holger Fröhlich | Zendy

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Learning gene network structure from time laps cell imaging in RNAi Knock downs

Author(s) -

Henrik Failmezger,

Paurush Praveen,

Achim Tresch,

Holger Fröhlich

Publication year - 2013

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/btt179

Subject(s) - bioconductor , rna interference , computer science , biological network , computational biology , gene regulatory network , markov chain monte carlo , markov chain , gene , gene silencing , biology , artificial intelligence , data mining , algorithm , genetics , machine learning , gene expression , rna , bayesian probability

As RNA interference is becoming a standard method for targeted gene perturbation, computational approaches to reverse engineer parts of biological networks based on measurable effects of RNAi become increasingly relevant. The vast majority of these methods use gene expression data, but little attention has been paid so far to other data types.

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