On the Modeling of Signaling Networks with Petri Nets

The whole-cell behavior arises from the interplay among signaling, metabolic, and regulatory processes. Proper modeling of the overall function requires accurate interpretations of each component. The highly concurrent nature of the inner-cell interactions motivates the use of Petri nets as a framework for the whole-cell modeling. Petri nets have been successfully used in modeling of metabolic pathways, as it allows for a straightforward mapping from its stoichiometric matrix to the Petri net structure. The Boolean interpretation and modeling of transcription regulation networks also lends itself easily to Petri net modeling. However, Petri net modeling of signal transduction networks has been largely lacking, with the exception of simple ad hoc applications to specific signaling pathways. In this thesis, I investigate the applicability of Petri nets to modeling of signaling networks, by systematically analyzing initial token assignments, firing strategies, and robustness to errors and abstractions in the estimates of molecule concentrations and reaction rates.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Engineering

Grantor

Rice University

Year dc:date.issued

2011

Author dc:creator

• Berestovsky, Natalia Sergeevna

Advisor dc:contributor.advisor

• Nakhleh, Luay K.

• Computer science

Statement dc:rights

• Copyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1911/64384

OAI identifier oai:identifier

oai:repository.rice.edu:1911/64384