ArticlePloS one2017
F-MAP: A Bayesian approach to infer the gene regulatory network using external hints.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- SimMapNet: a Bayesian framework for gene regulatory network inference using gene ontology similarities as external hint.BMC bioinformatics · 2026Article
- Article
- Identifying large-scale interaction atlases using probabilistic graphs and external knowledge.Journal of clinical and translational science · 2022Article
- Towards a Dynamic Interaction Network of Life to unify and expand the evolutionary theory.BMC biology · 2018Review
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Authors and funding
4 authors.
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Abstract
The Common topological features of related species gene regulatory networks suggest reconstruction of the network of one species by using the further information from gene expressions profile of related species. We present an algorithm to reconstruct the gene regulatory network named; F-MAP, which applies the knowledge about gene interactions from related species. Our algorithm sets a Bayesian framework to estimate the precision matrix of one species microarray gene expressions dataset to infer the Gaussian Graphical model of the network. The conjugate Wishart prior is used and the information from related species is applied to estimate the hyperparameters of the prior distribution by using the factor analysis. Applying the proposed algorithm on six related species of drosophila shows that the precision of reconstructed networks is improved considerably compared to the precision of networks constructed by other Bayesian approaches.
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