A multiscale modelling framework based on P systems

TitleA multiscale modelling framework based on P systems
Publication TypeJournal Papers
Year of Publication2009
AuthorsRomero-Campero, F. J., Twycross J., Hongqing C., Blakes J., & Krasnogor N.
Journal TitleLecture Notes in Computer Science
ISBN Number978-3-540-95884-0
PublisherSpringer Berlin / Heidelberg
Volume5391
Pages63-77
Date Published01/2009
Abstract

Cellular systems present a highly complex organization at different scales including the molecular, cellular and colony levels. The complexity at each one of these levels is tightly interrelated. Integrative systems biology aims to obtain a deeper understanding of cellular systems by focusing on the systemic and systematic integration of the different levels of organization in cellular systems.
The different approaches in cellular modeling within systems biology have been classified into mathematical and computational frameworks. Specifically, the methodology to develop computational models has been recently called executable biology since it produces executable algorithms whose computations resemble the evolution of cellular systems.
In this work we present P systems as a multiscale modeling framework within executable biology. P system models explicitly specify the molecular, cellular and colony levels in cellular systems in a relevant and understandable manner. Molecular species and their structure are represented by objects or strings, compartmentalization is described using membrane structures and finally cellular colonies and tissues are modeled as a collection of interacting individual P systems.
The interactions between the components of cellular systems are described using rewriting rules. These rules can in turn be grouped together into modules to characterize specific cellular processes. One of our current research lines focuses on the design of cell systems biology models exhibiting a prefixed behavior through the automatic assembly of these cellular modules. Our approach is equally applicable to synthetic as well as systems biology.

URLhttp://www.springerlink.com/content/n226127713438106/
DOI10.1007/978-3-540-95885-7_5