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Other titles in the Lecture Notes in Computer Science: Journal Subline series:
Lecture Notes in Computer Science: Journal Subline #6575: Transactions on Computational Systems Biology XIIIby Corrado Priami
Synopses & Reviews
The LNCS journal Transactions on Computational Systems Biology is devoted to inter- and multidisciplinary research in the fields of computer science and life sciences and supports a paradigmatic shift in the techniques from computer and information science to cope with the new challenges arising from the systems oriented point of view of biological phenomena. This, the 13th Transactions on Computational Systems Biology volume, guest edited by Ralph-Johan Back, Ion Petre, and Erik de Vink, focuses on Computational Models for Cell Processes and features a number of carefully selected and enhanced contributions initially presented at the CompMod workshop, which took place in Eindhoven, The Netherlands, in November 2009. From different points of view and following various approaches, the papers cover a wide range of topics in systems biology, addressing the dynamics and the computational principles of this emerging field.
This book covers Computational Models for Cell Processes, featuring enhanced contributions from the CompMod workshop (2009). Covers a wide range of topics in systems biology, addressing the dynamics and the computational principles of this emerging field.
Table of Contents
Evolutionary Dynamics of a Population of Cells with a Toxin Suppressor Gene.- Translation from the Quantified Implicit Process Flow Abstraction in SBGN-PD Diagrams to Bio-PEPA Illustrated on the Cholesterol Pathway.- Impulse-Based Dynamic Simulation of Deformable Biological Structures.- Delay Stochastic Simulation of Biological Systems: A Purely Delayed Approach.- Modelling Ammonium Transporters in Arbuscular Mycorrhiza Symbiosis.- Genetically Regulated Metabolic Networks: Gale-Nikaido Modules and Differential Inequalities.- Cultural Epigenetics: On the Heritability of Complex Diseases.- Refining Dynamics of Gene Regulatory Networks in a Stochastic π-Calculus Framework.
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