Integration of Computational Techniques for the Modelling of Signal Transduction

TL;DR

This paper introduces Cellulat, an agent-based model integrating computational techniques to simulate intracellular signal transduction, emphasizing cognitive functions and spatial organization, demonstrated through the EGFR pathway.

Contribution

It presents a novel intracellular signalling model combining multiple computational methods within an agent-based framework, highlighting cognitive and spatial aspects.

Findings

Successful modelling of EGFR signalling pathway

Demonstration of a virtual laboratory for intracellular signalling

Integration of cognitive and spatial features in signal transduction

Abstract

A cell can be seen as an adaptive autonomous agent or as a society of adaptive autonomous agents, where each can exhibit a particular behaviour depending on its cognitive capabilities. We present an intracellular signalling model obtained by integrating several computational techniques into an agent-based paradigm. Cellulat, the model, takes into account two essential aspects of the intracellular signalling networks: cognitive capacities and a spatial organization. Exemplifying the functionality of the system by modelling the EGFR signalling pathway, we discuss the methodology as well as the purposes of an intracellular signalling virtual laboratory, presently under development.