Deterministic Versus Stochastic Modelling in Biochemistry and Systems Biology

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 system. 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.

• List of figuresList of tablesPrefaceAbout the Authors and ContributorsChapter 1: Deterministic chemical kineticsAbstract:1.1 Determinism and Chemistry1.2 The Material Balance1.3 The Rate Law1.4 Solving the Conservation Equations1.5 Simple Reaction Mechanisms1.6 The Law of Mass Action1.7 ConclusionsChapter 2: The stochastic approach to biochemical kineticsAbstract:2.1 Introduction2.2 The chemical master equation2.3 Solution of the Master EquationThe irreversible reaction A → BThe Irreversible Reaction A + B → COther Irreversible Bimolecular ReactionsThe reversible reaction A + B C at equilibriumOther reversible bimolecular reactions at equilibrium2.4 The relationship between the deterministic and stochastic formalismsChapter 3: The exact stochastic simulation algorithmsAbstract.3.1 Introduction3.2 The reaction probability density function3.3 The stochastic simulation algorithms3.4 Case studies3.5 Caveats regarding the modeling of living systemsChapter 4: Modelling in systems biologyAbstract4.1 What is biological modeling4.2 System Biology4.3 Complexity of a biological system4.4 Stochastic modeling approach4.5 Formalizing complexityChapter 5: The structure of biochemical modelsAbstract5.1 Classification of biological processes and mathematical formalism5.2 Spatially Homogeneous Models5.3 Variants of the SSA for non-Markovian and non-homogeneous processesChapter 6: Reaction-diffusion systemsAbstract6.1 Introduction6.2 A generalization of the Fick’s law6.3 The optimal size of the system’s subvolumes6.4 The algorithm and data structure6.5 Case study 1: chaperone-assisted folding6.6 Case study 2: modeling the formation of Bicoid gradient6.7 Conclusions and future directionsChapter 7: KInfer: a tool for model calibrationAbstract7.1 Introduction7.2 The model for inference7.3 Synthetic case study: buffering SERCA pump7.4 Real case studies7.5 Glucose metabolisms of Lactococcus lactis7.6 DiscussionChapter 8: Modelling living systems with BlenXAbstract8.1 Deterministic vs stochastic approach in systems biology8.2 The BlenX language8.3 The ubiquitin-proteasome system8.4 A predator-prey model8.5 ConclusionsChapter 9: Simulation of ecodynamics: key nodes in food websAbstract9.1 Systems ecology9.2 Ecological interaction networks9.3 Pattern and process9.4 Food web dynamics: simulation and sensitivity analysisNotesIndex