ReviewEssays in biochemistry2008
Modelling reaction kinetics inside cells.
Review in Essays in biochemistry, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Antechokinetics, the kinetics of antimicrobial resistance molecules.Frontiers in pharmacology · 2026Review
- Integration Approaches to Model Bioreactor Hydrodynamics and Cellular Kinetics for Advancing Bioprocess Optimisation.Bioengineering (Basel, Switzerland) · 2024Review
- Divalent ligand-monovalent molecule binding.Soft matter · 2021Article
- Quantifying the roles of space and stochasticity in computer simulations for cell biology and cellular biochemistry.Molecular biology of the cell · 2021Article
- Stochastic master equation for early protein aggregation in the transthyretin amyloid disease.Scientific reports · 2020Article
- Spatial Stochastic Intracellular Kinetics: A Review of Modelling Approaches.Bulletin of mathematical biology · 2019Review
- Linear mapping approximation of gene regulatory networks with stochastic dynamics.Nature communications · 2018Article
- Kinetic Analysis Reveals the Identity of Aβ-Metal Complex Responsible for the Initial Aggregation of Aβ in the Synapse.ACS chemical neuroscience · 2017Article
- Evaluation of rate law approximations in bottom-up kinetic models of metabolism.BMC systems biology · 2016Article
- Closed-form stochastic solutions for non-equilibrium dynamics and inheritance of cellular components over many cell divisions.Proceedings. Mathematical, physical, and engineering sciences · 2015Article
- Validity conditions for stochastic chemical kinetics in diffusion-limited systems.The Journal of chemical physics · 2014Article
- Mathematical models light up plant signaling.The Plant cell · 2014Review
- Effects of bursty protein production on the noisy oscillatory properties of downstream pathways.Scientific reports · 2013Article
- A protein turnover signaling motif controls the stimulus-sensitivity of stress response pathways.PLoS computational biology · 2013Article
- Article
- Logic-based models in systems biology: a predictive and parameter-free network analysis method.Integrative biology : quantitative biosciences from nano to macro · 2012Review
- Mathematical simulation of membrane protein clustering for efficient signal transduction.Annals of biomedical engineering · 2012Review
- Stochastic branching-diffusion models for gene expression.Proceedings of the National Academy of Sciences of the United States of America · 2012Article
- Intrinsic noise analyzer: a software package for the exploration of stochastic biochemical kinetics using the system size expansion.PloS one · 2012Article
- A framework for modeling the relationship between cellular steady-state and stimulus-responsiveness.Methods in cell biology · 2012Article
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Authors and funding
2 authors.
Funding
Abstract
In the past decade, advances in molecular biology such as the development of non-invasive single molecule imaging techniques have given us a window into the intricate biochemical activities that occur inside cells. In this chapter we review four distinct theoretical and simulation frameworks: (i) non-spatial and deterministic, (ii) spatial and deterministic, (iii) non-spatial and stochastic and (iv) spatial and stochastic. Each framework can be suited to modelling and interpreting intracellular reaction kinetics. By estimating the fundamental length scales, one can roughly determine which models are best suited for the particular reaction pathway under study. We discuss differences in prediction between the four modelling methodologies. In particular we show that taking into account noise and space does not simply add quantitative predictive accuracy but may also lead to qualitatively different physiological predictions, unaccounted for by classical deterministic models.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.