CLUE: Exact maximal reduction of kinetic models by constrained lumping of differential equations

@article{Ovchinnikov2020CLUEEM,
  title={CLUE: Exact maximal reduction of kinetic models by constrained lumping of differential equations},
  author={Alexey Ovchinnikov and Isabel Christina P{\'e}rez-Verona and Gleb Pogudin and Mirco Tribastone},
  journal={Bioinformatics},
  year={2020}
}
MOTIVATION Detailed mechanistic models of biological processes can pose significant challenges for analysis and parameter estimations due to the large number of equations used to track the dynamics of all distinct configurations in which each involved biochemical species can be found. Model reduction can help tame such complexity by providing a lower-dimensional model in which each macro-variable can be directly related to the original variables. RESULTS We present CLUE, an algorithm for… 

Figures and Tables from this paper

Efficient Local Computation of Differential Bisimulations via Coupling and Up-to Methods

An algorithm for the computation of equivalence relations which can be interpreted as a lifting of probabilistic bisimulation to polynomial differential equations, a ubiquitous model of dynamical systems across science and engineering is developed.

Interpretable exact linear reductions via positivity

An algorithm is designed and implemented that, given an exact linear reduction of the smallest possible dimension, re-parametrizes it by performing an invertible transformation of the new coordinates to improve the interpretability of thenew variables.

Dynamical Systems of Differential Equations Based on Information Technology: Effects of Integral Step Size on Bifurcation and Chaos Control of Discrete Hindmarsh–Rose Models

  • Xueli Chen
  • Computer Science
    Mobile Information Systems
  • 2022
This article understands how the integral step affects the bifurcation and chaos control of the discrete Hindmarsh–Rose model by choosing the appropriate step size.

Exact linear reduction for rational dynamical systems

Detailed dynamical systems models used in life sciences may include dozens or even hundreds of state variables. Models of large dimension are not only harder from the numerical perspective (e.g., for

References

SHOWING 1-10 OF 47 REFERENCES

Reduction of a biochemical model with preservation of its basic dynamic properties

A comparative study of two different methods applied to a 20D model of yeast glycolytic oscillations, using lumping and subsequent constrained parameter optimization and a novel approach that eliminates variables not essential for the dynamics.

A method for zooming of nonlinear models of biochemical systems

This paper introduces a novel method for reduction of biochemical models that is compatible with the concept of zooming, and extends the applicability of the method that was previously developed for zooming of linear biochemical models to nonlinear models.

A Large-Scale Assessment of Exact Model Reduction in the BioModels Repository

A family of techniques for both deterministic and stochastic networks which are based on equivalence relations over the species in the network are considered, leading to a coarse graining which provides the exact aggregate time-course evolution for each equivalence class.

Maximal aggregation of polynomial dynamical systems

An aggregation technique that rests on two notions of equivalence relating ODE variables whenever they have the same solution (backward criterion) or if a self-consistent system can be written for describing the evolution of sums of variables in the same equivalence class (forward criterion).

Complexity reduction of biochemical rate expressions

This work presents a new reduction method that reduces complex rational rate expressions, such as those often used to describe enzymatic reactions, which is one of the first methods to meet the classical engineering objective of improved parameter identifiability without losing the systems biology demand of preserved biochemical interpretation.

Methods of Model Reduction for Large-Scale Biological Systems: A Survey of Current Methods and Trends

A brief mathematical account of the main methods of model reduction including timescale exploitation approaches, reduction via sensitivity analysis, optimisation methods, lumping, and singular value decomposition-based approaches are provided.

Lumping in Pharmacokinetics

The lumping methods presented here can be easily automated, and are applicable to first-order ordinary differential equation systems, and the potential of such methods in toxico/pharmacokinetics is studied.

A general analysis of exact lumping in chemical kinetics