Modelling the influence of RKIP on the ERK signalling pathway using the stochastic process algebra PEPA

This paper examines the influence of the Raf Kinase Inhibitor Protein (RKIP) on the Extracellular signal Regulated Kinase (ERK) signalling pathway [5] through modelling in a Markovian process algebra, PEPA [11]. Two models of the system are presented, a reagent-centric view and a pathway-centric view. The models capture functionality at the level of subpathway, rather than at a molecular level. Each model affords a different perspective of the pathway and analysis. We demonstrate the two models to be formally equivalent using the timing-aware bisimulation defined over PEPA models and discuss the biological significance

Mitigation and adaptation strategies for global change : an international journal devoted to scientific, engineering, socio-economic and policy responses to environmental change

Abstract. The classic view of metabolism as a collection of metabolic pathways is being questioned with the currently available possibility of studying whole networks. Novel ways of decomposing the network into modules and motifs that could be considered as the building blocks of a network are being suggested. In this work, we introduce a new definition of motif in the context of metabolic networks. Unlike in previous works on (other) biochemical networks, this definition is not based only on topological features. We propose instead to use an alternative definition based on the functional nature of the components that form the motif. After introducing a formal framework motivated by biological considerations, we present complexity results on the problem of searching for all occurrences of a reaction motif in a network, and introduce an algorithm that is fast in practice in most situations. We then show an initial application to the study of pathway evolution.

Modelling inhibition in metabolic pathways through abduction and induction

Abstract. In this paper, we study how a logical form of scientific modelling that integrates together abduction and induction can be used to understand the functional class of unknown enzymes or inhibitors. We show how we can model, within Abductive Logic Programming (ALP), inhibition in metabolic pathways and use abduction to generate facts about inhibition of enzymes by a particular toxin (e.g. Hydrazine) given the underlying metabolic pathway and observations about the concentration of metabolites. These ground facts, together with biochemical background information, can then be generalised by ILP to generate rules about the inhibition by Hydrazine thus enriching further our model. In particular, using Progol 5.0 where the processes of abduction and inductive generalization are integrated enables us to learn such general rules. Experimental results on modelling in this way the effect of Hydrazine in a real metabolic pathway are presented.