Inferring Intracellular Signal Transduction Circuitry from Molecular Perturbation Experiments.

ABSTRACT: The development of network inference methodologies that accurately predict connectivity in dysregulated pathways may enable the rational selection of patient therapies. Accurately inferring an intracellular network from data remains a very challenging problem in molecular systems biology. Living cells integrate extremely robust circuits that exhibit significant heterogeneity, but still respond to external stimuli in predictable ways. This phenomenon allows us to introduce a network inference methodology that integrates measurements of protein activation from perturbation experiments. The methodology relies on logic-based networks to provide a predictive approximation of the transfer of signals in a network. The approach presented was validated in silico with a set of test networks and appl

SUBMITTER: Wynn ML 

PROVIDER: S-EPMC5660674 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature