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IPM
30
YEARS OLD

“School of Biological Sciences”

Paper   IPM / Biological Sciences / 14978
   School of Biological Sciences
  Title: F-MAP: A Bayesian approach to infer the gene regulatory network using external hints
  Author(s):
1 . Maryam Shahdoust
2 . Hamid Pezeshk
3 . Hossein Mahjub
4 . Mehdi Sadeghi
  Status: Published
  Journal: PlosOne
  No.: 9
  Vol.: 19
  Year: 2017
  Pages: https://doi.org/10.1371/journal.pone.0184795
  Supported by: IPM
  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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