Strategy-Driven Exploration for Rule-Based Models of Biochemical Systems with Porgy

Abstract

This paper presents Porgy-an interactive visual environment for rule-based modelling of biochemical systems. We model molecules and molecule interactions as port graphs and port graph rewrite rules, respectively. We use rewriting strategies to control which rules to apply, and where and when to apply them. Our main contributions to rule-based modelling of biochemical systems lie in the strategy language and the associated visual and interactive features offered by Porgy. These features facilitate an exploratory approach to test different ways of applying the rules while recording the model evolution, and tracking and plotting parameters. We illustrate Porgy's features with a study of the role of a scaffold protein in Raf-1/MEK/ERK signalling.

A Strategic Graph Rewriting Model of Rational Negligence in Financial Markets

“…A variety of GTS tools are available: among others we can cite GROOVE [19], a graph-based model checker for object oriented systems; AGG (the Attributed Graph Grammar System) [31], a graph-based language for the transformation of attributed graphs that comes with a visual programming environment; PROGRES (Programmed Graph Rewriting Systems) [29] that offers backtracking and nondeterministic constructs; GrGen (Graph Rewrite Generator) [18] that uses attributed typed multigraphs and includes features such as Java/C code generation, and GP [28], a graph programming language, where users can define rules and strategy expressions, with support for conditional rewriting. PORGY [14] has been used to model social networks [15] and database design [34,16], as well as biochemical processes [2], where non-determinism, backtracking, positioning constructs, and probabilistic rule application are key features. A distinctive feature of PORGY is that rewriting derivations are directly available to users via the so-called derivation tree, which provides a visual representation of the dynamics of the system modelled and can be used to plot parameters and generate charts as illustrated in Section 4.…”

Ten simple rules to create biological network figures for communication

“…To be legible, labels in the figure should use the same (or larger) font size as the caption font, not smaller. Fig 4A shows PPI data from Andrei and colleagues [34], in which the node labels are too small to be legible. In Fig 4B, the layout has been modified to make better use of the available space, resulting in larger labels.…”

“…(A) An example network based on PPI data from Andrei and colleagues [34], in which the node labels are too small to be legible. (B) The same network, but this time the layout has been improved to make better use of the available space, resulting in larger labels.…”

Modelling and Verifying Dynamic Properties of Biological Neural Networks in Coq

“…In [19], the authors advocate the use of higher-order logic to formalize reaction kinetics and exploit the HOL Light theorem prover to verify some reaction-based models of biological networks. Finally, the Porgy system is introduced in [20]. It is a visual environment which allows modelling of biochemical systems as rule-based models.…”