Contact: sasb2012@easychair.org
Postproceedings have been published in ENTCS:
A lot of biological models suffer from a high combinatorial complexity.
Many methods have been proposed to break down this combinatorial
complexity.
Some of these methods are informal and are validated experimentally.
By contrast, static analysis-based scalable formal methods increase the level of confidence by providing formal characterization of what is computed. Being automatic, easily reusable, and offering formal soundness criteria, static analyses can help designing models, testing models with respect to experimental data, and predicting the behavior of the system being modeled.
The goal of this workshop is to promote discussions and collaborations between biologists (modelers), computer scientists (in static analysis) and applied-mathematicians around the design and the use of static analysis methods for biological models.
The third SASB will be co-located with SAS 2012 in Deauville, France.
Please visit the submission website.
The program of SASB 2012 will consist mainly of presentations of refereed papers. Contributions are welcomed on all aspects about the use of static analysis methods in Systems Biology, including, but not limited to:
All submitted papers will be peer-reviewed by the program committee.
Submitted papers should not exceed 12 pages including bibliography, and follow the ENTCS guidelines. Submitted papers may include, in addition, an appendix containing technical details, which reviewers may read or not, at their discretion.
Papers must be written and presented in English, and describe original work that does not substantially overlap with papers that have been published or that are simultaneously submitted to a journal, conference, or workshop with refereed proceedings.
All submitted posters will be peer-reviewed by the program committee.
Poster format is free with the stipulation that the size should not exceed A0 size (32.7 by 45.4 inches or 80 by 115.4 cm) in portrait (vertical) set-up. Moreover, the text must be written in English. A PDF version of the poster is required at the submission.
Submission Deadline (extended) | 15th June 2012 |
Notification (tentative) | 15th July 2012 |
Final version (tentative) | 15th August 2012 |
Submission Deadline | 15th June 2012 |
Notification (tentative) | 15th July 2012 |
Workshop Date | 10th September 2012 |
Jérôme Feret | École Normale Supérieure & INRIA, France |
Andre Levchenko | Institute for Computational Medecine, Johns Hopkins University, USA |
François Fages | INRIA, France |
Domitille Heitzler | Systems Biology Ireland, Ireland |
Jean Krivine | CNRS & Université Paris-Diderot, France |
Nathan Lemons | Los Alamos National Laboratory, USA |
Cédric Lhoussaine | Université de Lille 1, France |
Gethin Norman | University of Glasgow, Scottland |
Loïc Paulevé | Ecole polytechique, France |
Tatjana Petrov | ETH Zurich, Switzerland |
Franck Pommereau | Université d'Évry, France |
Ovidiu Radulescu | University of Montpellier 2, France |
Alessandro Romanel | University of Trento, Italy | Denis Thieffry | École Normale Supérieure, France |
Ty Thomson | Selventa, Boston, USA |
Paolo Zuliani | Carnegie Mellon University, USA |
Radhia Cousot | École Normale Supérieure & CNRS, France |
Jérôme Feret | École Normale Supérieure & INRIA, France |
Walter Fontana | Harvard Medical School, USA |
Andre Levchenko | Institute for Computational Medicine, Johns Hopkins University, USA |
8:30-9:15: Welcome coffee
9:15-10:15: First Invited Talk
10:45-12:05: Contributed talks, Session 1
15:45-16:25: Poster session
Cell have evolved complex signal transduction networks endowing them with the ability to sense and respond to a diverse set of environmental cues. It has become progressively clear that these signaling networks yield probabilistic rather than fully deterministic information about the input magnitude. Nevertheless, individual cell can frequently convert noisy signaling into a precisely defined decision, assuming a defined phenotype. In this talk, I will review our recent experimental results on how such robust decoding can be achieved. I will also suggest that the task is further complicated by multiplexing of signals through common nodes and by highly noisy network behavior. I will furthermore outline how the deterministic and stochastic aspects of signal processing can be combined within a single probabilistic model, which is highly predictive of complex multicellular responses.
We will discuss the general concept of 'executable knowledge', with particular emphasis on its application to the study of signaling pathways in cell biology, and the specific approach of 'rule-based modeling' in Kappa. We will review the novel analyses -- notably the use of static analysis and causality -- of complex systems that this enables, but also consider the difficulties that arise and present some partial solutions to these. The discussion will be organized around the running example of the use of Kappa to model the erbB receptor network.