Reduction of dynamical biochemical reaction networks in computational biology

Abstract

Biochemical networks are used in computational biology, to model the static and dynamical details of systems involved in cell signaling, metabolism, and regulation of gene expression. Parametric and structural uncertainty, as well as combinatorial explosion are strong obstacles against analyzing the dynamics of large models of this type. Multi-scaleness is another property of these networks, that can be used to get past some of these obstacles. Networks with many well separated time scales, can be reduced to simpler networks, in a way that depends only on the orders of magnitude and not on the exact values of the kinetic parameters. The main idea used for such robust simplifications of networks is the concept of dominance among model elements, allowing hierarchical organization of these elements according to their effects on the network dynamics. This concept finds a natural formulation in tropical geometry. We revisit, in the light of these new ideas, the main approaches to model reduction of reaction networks, such as quasi-steady state and quasi-equilibrium approximations, and provide practical recipes for model reduction of linear and nonlinear networks. We also discuss the application of model reduction to backward pruning machine learning techniques.

References in corpus (3)

• Method of invariant manifold for chemical kinetics
• Asymptotology of Chemical Reaction Networks
• Dynamic and static limitation in multiscale reaction networks, revisited

Cited by in corpus (17)

• Self-Organized Criticality and Pattern Emergence through the lens of Tropical Geometry
• Dichotomous noise models of gene switches
• Coarse graining of biochemical systems described by discrete stochastic dynamics
• Model composition through model reduction: a combined model of CD95 and NF-κB signaling pathways
• Statistical physics approaches to subnetwork dynamics in biochemical systems
• Quasisolitons in self-diffusive excitable systems, or Why asymmetric diffusivity does not violate the Second Law
• Algorithmic Reduction of Biological Networks With Multiple Time Scales
• Michaelis-Menten dynamics in protein subnetworks
• A Constraint Solving Approach to Tropical Equilibration and Model Reduction
• Extended Differential Aggregations in Process Algebra for Performance and Biology
• Universal Slow Dynamics of Chemical Reaction Networks
• Systematic model reduction captures the dynamics of extrinsic noise in biochemical subnetworks
• Reduction for asynchronous Boolean networks: elimination of negatively autoregulated components
• Dealing with complexity of biological systems: from data to models
• Comprehensive review of models and methods for inferences in bio-chemical reaction networks
• Iterative Approximate Solutions of Kinetic Equations for Reversible Enzyme Reactions
• Symbolic dynamics of biochemical pathways as finite states machines