(redirected from BME.PetriNets2010)
A satellite event of Petri Nets 2010 - Braga, Portugal, June 21, 2010
Jorge Carneiro, Instituto Gulbenkian de Ciência, IGC, Oeiras, Portugal
Why aren't Petri nets widely used in biological research?
Many cellular and supra-cellular processes are stochastic and combinatorial in nature. Binding of transcriptional factors to gene promoters or enhancers, context-dependent multistep epigenetic modifications of gene loci, regulation of ion channel gating, and multicellular interactions controlling cell differentiation and cycle are examples of fundamental stochastic processes that involve multiple intertwined concurrent events.
Designing and analysing models of such systems is a challenging and pains-taking task, since the number of variables and potential events increases exponentially with the number of relevant components one is willing to include in the model. Like in any modelling exercise these systems involve a trade-off between simplicity and realism, but, here, inadvertent omissions or oversimplifications in early model design are paid a too high price when redesign is necessary. The stochastic Petri nets (SPN) formalism is almost ideal to deal with these modelling difficulties, since it offers an intuitive and straightforward representation of interactions and concurrent events, and provides a solid theoretical framework to analyse the model structure and dynamics. Furthermore, several SPN software tools are available that allow a modeller to rapidly draw, modify, and analyse model variants. This "rapid prototyping" of a model facilitates the tasks of pruning away unnecessary components and identifying missing ones.
Considering these advantages of the use of SPN it is almost surprising that this formalism is not widely applied in modelling biological systems. Based on two examples of SPN application, namely to modelling somatic recombination of immune receptor genes and ion channel gating in sea urchin spermatozoa, I will argue that SPN software tools are well-suited for engineering artificial systems, but do not yet offer all the functionalities one would wish to have at hand when modelling a natural biological system.
Workshop Proceedings, ISBN: 978-972-8692-53-7
Jorge Carneiro, Invited talk:
Why aren't Petri nets widely used in biological research?
Cycle structure in SR and DSR graphs: implications for multiple equilibria and stable oscillation in chemical reaction networks
A corrected version of this paper is available at http://arxiv.org/abs/1005.5472.
Monika Heiner, Cristian Mahulea and Manuel Silva:
On the Importance of the Deadlock Trap Property for Monotonic Liveness
Laura M.F. Bertens, Jetty Kleijn, Maciej Koutny and Fons J. Verbeek:
Modelling Gradients Using Petri nets
Alessio Angius, Gianfranco Balbo, Francesca Cordero, Andras Horváth and Daniele Manini:
Comparison of approximate kinetics for unireactant enzymes: Michaelis-Menten against the equivalent server
Fei Liu and Monika Heiner:
Colored Petri nets to model and simulate biological systems
Roberto Ross-León, Antonio Ramirez-Treviño, José Alejandro Morales and Javier Ruiz-Leon:
Control Of Metabolic Systems Modeled with Timed Continuous Petri Nets
Daniel Machado, Rafael S. Costa, Miguel Rocha, Isabel Rocha, Bruce Tidor and Eugenio C. Ferreira:
Model transformation of metabolic networks using a Petri net based framework
Hermenegilda Macià, M. Isabel Gonzalez-Sanchez, Valentín Valero and Edelmira Valero:
Applying Petri nets for the analysis of the GSH-ASC cycle in chloroplasts
Mary Ann Blätke, Sonja Meyer, Christoph Stein and Wolfgang Marwan:
Petri Net Modeling via a Modular and Hierarchical Approach Applied to Nociception
Integrative biology, made possible by the spectacular growth of biological information, intends to decipher essential biological processes that are driven by complex mechanisms, involving miscellaneous interacting molecular compounds. In this context, the need for appropriate mathematical and computational modelling tools is widely advocated. Since about 15 years Petri nets have proved their usefulness for the modelling, analysis, and simulation of a diversity of biological networks, covering discrete, stochastic, continuous and hybrid models. The deployment of Petri nets to study biological applications has not only generated original models, but has also motivated fundamental research. Indeed, because of their complexity, size and heterogeneity, biological networks raise distinctive challenges to the modeller. The goal of this workshop is to provide a platform for researchers aiming at such fundamental research and real life applications.
Original and effective solutions are needed to study complex biological networks. As a matter of fact, while the biologists are now able to generate prodigious amounts of data, there is still an urgent need for dedicated computational and mathematical tools to decipher the control of complex cellular processes.
This workshop intends to gather researchers interested in the application of Petri nets for biological applications. Its main goal will be to demonstrate that this field of application raises new challenges for the Petri net community, and that Petri nets can be effective to tackle such challenges.
Full papers should be at most 15 p. in LNCS format, and will have to be submitted via EasyChair: http://www.easychair.org/conferences/?conf=bioppn2010. Submitted papers should describe original work that has not been previously published and is not under review for publication elsewhere. We also invite "work in progress" papers, which have to be indicated as such.
Short papers presenting original results should not exceed 6 pages in LNCS format, including figures, tables and references (submission via EasyChair: http://www.easychair.org/conferences/?conf=bioppn2010). Short papers may be selected for oral presentation.
Will be published by the hosting university.
Best papers will be proposed to be invited for the follow-up publication in Transactions on Petri Nets and other models of Concurrency (ToPNoC).
Instituto Gulbenkian de Ciência, IGC, Oeiras, Portugal
chaouiya (at) igc.gulbenkian.pt
Brandenburg University of Technology at Cottbus, Computer Science Institute, Germany
monika.heiner (at) informatik.tu-cottbus.de