Abstract: In this paper, we introduce a novel way of constructing concise causal histories (pathways) to represent how specified structures are formed during simulation of systems represented by rulebased models. This is founded on a new, clean, graph-based semantics introduced in the first part of this paper for Kappa, a rule-based modelling language that has emerged as a natural description of protein-protein interactions in molecular biology [1]. The semantics is capable of capturing the whole of Kappa, including subtle side-effects on deletion of structure, and its structured presentation provides the basis for the translation of techniques to other models. In particular, we give a notion of trajectory compression, which restricts a trace culminating in the production of a given structure to the actions necessary for the structure to occur. This is central to the reconstruction of biochemical pathways due to the failure of traditional techniques to provide adequately concise causal histories, and we expect it to be applicable in a range of other modelling situations.

@inproceedings{DBLP:conf/fsttcs/DanosFFHH12,
  author    = {Vincent Danos and J{\'e}r{\^o}me Feret and Walter Fontana and Russell Harmer and Jonathan Hayman and Jean Krivine and Christopher D. Thompson-Walsh and Glynn Winskel},
  title     = {Graphs, Rewriting and Pathway Reconstruction for Rule-Based Models},
  year      = {2012},
  pages     = {276-288},
  ee        = {http://dx.doi.org/10.4230/LIPIcs.FSTTCS.2012.276},
  editor    = {Deepak D'Souza and Telikepalli Kavitha and Jaikumar Radhakrishnan},
  booktitle     = {IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, FSTTCS 2012},
  publisher = {Schloss Dagstuhl - Leibniz-Zentrum f{\"u}r Informatik},
  series    = {LIPIcs},
  volume    = {18},
}