Ambiguity in logic-based models of gene regulatory networks: An integrative multi-perturbation analysis.

ABSTRACT: Most studies of gene regulatory network (GRN) inference have focused extensively on identifying the interaction map of the GRNs. However, in order to predict the cellular behavior, modeling the GRN in terms of logic circuits, i.e., Boolean networks, is necessary. The perturbation techniques, e.g., knock-down and over-expression, should be utilized for identifying the underlying logic behind the interactions. However, we will show that by using only transcriptomic data obtained by single-perturbation experiments, we cannot observe all regulatory interactions, and this invisibility causes ambiguity in our model. Consequently, we need to employ the data of multiple omics layers (genome, transcriptome, and proteome) as well as multiple perturbation experiments to reduce or eliminate ambiguity

SUBMITTER: Alizad-Rahvar AR 

PROVIDER: S-EPMC6245684 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature