1.
Annu Int Conf IEEE Eng Med Biol Soc
; 2016: 1471-1475, 2016 Aug.
Artigo
em Inglês
| MEDLINE
| ID: mdl-28268604
RESUMO
The problem of inferring a stochastic model for gene regulatory networks is addressed here. The prior biological data includes biological pathways and time-series expression data. We propose a novel algorithm to use both of these data to construct a Probabilistic Boolean Network (PBN) which models the observed dynamics of genes with a high degree of precision. Our algorithm constructs a pathway tree and uses the time-series expression data to select an optimal level of tree, whose nodes are used to infer the PBN.