ReviewComputational and structural biotechnology journal2014
Stochastic simulation in systems biology.
Review in Computational and structural biotechnology journal, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
24 citing papers in PubMed.
- Holimap: an accurate and efficient method for solving stochastic gene network dynamics.Nature communications · 2024Article
- Application of a novel numerical simulation to biochemical reaction systems.Frontiers in cell and developmental biology · 2024Article
- Fluorescent biosensor imaging meets deterministic mathematical modelling: quantitative investigation of signalling compartmentalization.The Journal of physiology · 2023Review
- Limits and Prospects of Molecular Fingerprinting for Phenotyping Biological Systems Revealed throughAnalytical chemistry · 2023Article
- Modeling Neurons in 3D at the Nanoscale.Advances in experimental medicine and biology · 2022Article
- FiCoS: A fine-grained and coarse-grained GPU-powered deterministic simulator for biochemical networks.PLoS computational biology · 2021Article
- Towards understanding the messengers of extracellular space: Computational models of outside-in integrin reaction networks.Computational and structural biotechnology journal · 2021Review
- Multiscale Computational Modeling of Vascular Adaptation: A Systems Biology Approach Using Agent-Based Models.Frontiers in bioengineering and biotechnology · 2021Review
- A mathematical modelling framework for the regulation of intra-cellular OCT4 in human pluripotent stem cells.PloS one · 2021Article
- Identifiability analysis for stochastic differential equation models in systems biology.Journal of the Royal Society, Interface · 2020Article
- Stochastic modeling of human papillomavirusearly promoter gene regulation.Journal of theoretical biology · 2020Article
- Estimating growth patterns and driver effects in tumor evolution from individual samples.Nature communications · 2020Article
- Discrete and continuous models of probability flux of switching dynamics: Uncovering stochastic oscillations in a toggle-switch system.The Journal of chemical physics · 2019Article
- Spatial Stochastic Intracellular Kinetics: A Review of Modelling Approaches.Bulletin of mathematical biology · 2019Review
- Hybrid stochastic framework predicts efficacy of prophylaxis against HIV: An example with different dolutegravir prophylaxis schemes.PLoS computational biology · 2018Article
- Diverse genetic error modes constrain large-scale bio-based production.Nature communications · 2018Article
- Therapeutic target discovery using Boolean network attractors: improvements of kali.Royal Society open science · 2018Article
- A stochastic and dynamical view of pluripotency in mouse embryonic stem cells.PLoS computational biology · 2018Article
- A Multi-stage Representation of Cell Proliferation as a Markov Process.Bulletin of mathematical biology · 2017Article
- LASSIE: simulating large-scale models of biochemical systems on GPUs.BMC bioinformatics · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Natural systems are, almost by definition, heterogeneous: this can be either a boon or an obstacle to be overcome, depending on the situation. Traditionally, when constructing mathematical models of these systems, heterogeneity has typically been ignored, despite its critical role. However, in recent years, stochastic computational methods have become commonplace in science. They are able to appropriately account for heterogeneity; indeed, they are based around the premise that systems inherently contain at least one source of heterogeneity (namely, intrinsic heterogeneity). In this mini-review, we give a brief introduction to theoretical modelling and simulation in systems biology and discuss the three different sources of heterogeneity in natural systems. Our main topic is an overview of stochastic simulation methods in systems biology. There are many different types of stochastic methods. We focus on one group that has become especially popular in systems biology, biochemistry, chemistry and physics. These discrete-state stochastic methods do not follow individuals over time; rather they track only total populations. They also assume that the volume of interest is spatially homogeneous. We give an overview of these methods, with a discussion of the advantages and disadvantages of each, and suggest when each is more appropriate to use. We also include references to software implementations of them, so that beginners can quickly start using stochastic methods for practical problems of interest.
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Registered trials
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.