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Deterministic versus stochastic modelling in biochemistry and systems biology
Woodhead Publishing Ltd, November 2012, Pages: 250
Stochastic kinetic methods are currently considered to be the most realistic and elegant means of representing and simulating the dynamics of biochemical and biological networks. Deterministic versus stochastic modelling in biochemistry and systems biology introduces and critically reviews the deterministic and stochastic foundations of biochemical kinetics, covering applied stochastic process theory for application in the field of modelling and simulation of biological processes at the molecular scale.
Deterministic chemical kinetics
- The stochastic approach to biochemical kinetics
- The exact stochastic simulation algorithms
- Modelling in systems biology
- The structure of biochemical models
- Reaction-diffusion systems
- KInfer: A tool for model calibration
- Modelling living systems with BlenX
- Simulation of ecodynamics: Key nodes in food webs.
Paola Lecca is a researcher at The Microsoft Research – University of Trento, Centre for Computational and Systems Biology, Italy. Her principal research interests include biochemical system identification and model calibration, stochastic chemical kinetics and reaction-diffusion systems.
Ian J. Laurenzi is a Senior Researcher at ExxonMobil. He is an expert in the areas of stochastic processes, statistics, computational biology and receptor-mediated adhesion of human blood platelets, and has investigated the genome-level dynamics of gene networks and the effect of sex upon mammalian gene expression
Ferenc Jordan is a biologist whose background is in genetics, theoretical biology and evolutionary biology, and his principal recent interests are systems ecology and biological networks.