Rule-Based Modelling and Model Perturbation

被引:0
|
作者
Danos, Vincent [1 ]
Feret, Jerome [2 ]
Fontana, Walter [3 ]
Harmer, Russ [4 ,5 ]
Krivme, Jean [3 ]
机构
[1] Univ Edinburgh, Edinburgh EH8 9YL, Midlothian, Scotland
[2] INRIA ENS CNRS, Paris, France
[3] Harvard Medical School, Boston, MA USA
[4] Institut des Hautes Etudes Scientifiques, Bures Sur Yvette, France
[5] Univ Paris, CNRS, Paris, France
关键词
GROWTH-FACTOR RECEPTOR; CELLULAR SIGNALING NETWORKS; KINASE DOMAIN; ACTIVATION; INHIBITION; PATHWAY; BINDING;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Rule-based modelling has already proved to be successful for taming the combinatorial complexity typical of cellular signalling networks. caused by the combination of physical protein-protein interactions and modifications that generate astronomical numbers of distinct molecular species However, traditional rule-based approaches, based on an unstructured space of agents and rules, remain susceptible to other combinatorial explosions caused by imitated and/or splice variant agents. that share most but not all of their rules with their wild-type counter parts and by drugs, which must: be clearly distinguished from physiological ligands In this paper, we define a syntactic extension of Kappa, an established rule-based modelling platform, that enables the expression of a structured space of agents and rules that allows us to express mutated agents, splice variants, families of related proteins and ligand/drug interventions uniformly. This also enables a anode of model construction where, starting from the current consensus model, we attempt to reproduce in numero the mutational and more generally the ligand/drug perturbational analyses that were used in the process of inferring those pathways in the first place.
引用
收藏
页码:116 / +
页数:4
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