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Robust data-driven incorporation of prior knowledge into the inference of dynamic regulatory networks

Motivation: Inferring global regulatory networks (GRNs) from genome-wide data is a computational challenge central to the field of systems biology. Although the primary data currently used to infer GRNs consist of gene expression and proteomics measurements, there is a growing abundance of alternate...

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Détails bibliographiques
Auteurs principaux: Greenfield, Alex, Hafemeister, Christoph, Bonneau, Richard
Format: Artigo
Langue:Inglês
Publié: Oxford University Press 2013
Sujets:
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC3624811/
https://ncbi.nlm.nih.gov/pubmed/23525069
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btt099
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