Correcting for link loss in causal network inference caused by regulator interference | Zendy

Ying Wang | Zendy; Christopher A. Penfold | Zendy; David A. Hodgson | Zendy; Miriam L. Gifford | Zendy; Nigel J. Burroughs | Zendy

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Correcting for link loss in causal network inference caused by regulator interference

Author(s) -

Ying Wang,

Christopher A. Penfold,

David A. Hodgson,

Miriam L. Gifford,

Nigel J. Burroughs

Publication year - 2014

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btu388

Subject(s) - interference (communication) , regulator , inference , causal inference , computer science , link (geometry) , expression (computer science) , construct (python library) , computer network , mathematics , artificial intelligence , econometrics , biology , gene , biochemistry , channel (broadcasting) , programming language

There are a number of algorithms to infer causal regulatory networks from time series (gene expression) data. Here we analyse the phenomena of regulator interference, where regulators with similar dynamics mutually suppress both the probability of regulating a target and the associated link strength; for instance, interference between two identical strong regulators reduces link probabilities by ∼50%.

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