[Colloq] Reminder: Talk, Monday, February 11 - Vincent Danos

[Rachel Kalweit]

College of Computer and Information Science Colloquium

Presents:
Vincent Danos

Who will speak on:
“Rule-based Modeling of Cellular Signaling” 
[Joint work with Jerome Feret, Walter Fontana, Russell Harmer, and Jean Krivine]

Monday, February 11, 2008
12:00 pm
366 West Village H
Northeastern University


Abstract:
Modeling is becoming a necessity in studying biological signaling pathways, because the combinatorial complexity of such systems rapidly overwhelms intuitive and qualitative forms of reasoning. Yet, this same combinatorial explosion makes the traditional modeling paradigm based on systems of differential equations impractical. In contrast, agent-based or concurrent languages, such as Kappa or the closely related BioNetGen language describe biological interactions in terms of rules, thereby avoiding the combinatorial explosion besetting differential equations. Rules are expressed in an intuitive graphical form that transparently represents biological knowledge. In this way, rules become a natural unit of model building, modification, and discussion. We illustrate this with a sizeable example obtained from refactoring two models of EGF receptor signaling that are based on differential equations. An exciting aspect of the agent-based approach is that it naturally lends itself to the identification and analysis of the causal structures that deeply shape the dynamical, and perhaps even evolutionary, characteristics of complex distributed biological systems. In particular, one can adapt the notions of causality and conflict, familiar from concurrency theory, to Kappa, our representation language of choice. Using the EGF receptor model as an example, we show how causality enables the formalization of the colloquial concept of pathway and, perhaps more surprisingly, how conflict can be used to dissect the signaling dynamics to obtain a qualitative handle on the range of system behaviors. By taming the combinatorial explosion, and exposing the causal structures and key kinetic junctures in a model, agent- and rule-based representations hold promise for making modeling more powerful, more perspicuous, and of appeal to a wider audience.

Host: Karl Lieberherr



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