Supervised, semi-supervised and unsupervised inference of gene regulatory networks.
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ABSTRACT:
SUBMITTER: Maetschke SR
PROVIDER: S-EPMC3956069 | biostudies-literature | 2014 Mar
REPOSITORIES: biostudies-literature
Publications
Supervised, semi-supervised and unsupervised inference of gene regulatory networks.
Maetschke Stefan R SR Madhamshettiwar Piyush B PB Davis Melissa J MJ Ragan Mark A MA
Briefings in bioinformatics 20130521 2
Inference of gene regulatory network from expression data is a challenging task. Many methods have been developed to this purpose but a comprehensive evaluation that covers unsupervised, semi-supervised and supervised methods, and provides guidelines for their practical application, is lacking. We performed an extensive evaluation of inference methods on simulated and experimental expression data. The results reveal low prediction accuracies for unsupervised techniques with the notable exception ...[more]
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