Reconstruction of extended Petri nets from time series data and its application to signal transduction and to gene regulatory networks.

ABSTRACT:

Background

Network inference methods reconstruct mathematical models of molecular or genetic networks directly from experimental data sets. We have previously reported a mathematical method which is exclusively data-driven, does not involve any heuristic decisions within the reconstruction process, and deliveries all possible alternative minimal networks in terms of simple place/transition Petri nets that are consistent with a given discrete time series data set.

Results

We fundamentally extended the previously published algorithm to consider catalysis and inhibition of the reactions that occur in the underlying network. The results of the reconstruction algorithm are encoded in the form of an extended Petri net involving control arcs. This allows the consideration of proces

SUBMITTER: Durzinsky M 

PROVIDER: S-EPMC3161898 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature