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Multi-state Modeling of Biomolecules
2014
PLoS Computational Biology
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Multi-state modeling of biomolecules refers to a series of techniques used to represent and compute the behavior of biological molecules or complexes that can adopt a large number of possible functional ...
equations, partial differential equations, or the Gillespie stochastic simulation algorithm [9,10]. ...
Acknowledgments The version history of the text file and the peer reviews (and response to reviews) are available as supporting information in Text S1 and S2. ...
doi:10.1371/journal.pcbi.1003844
pmid:25254957
pmcid:PMC4201162
fatcat:7myvop47lvhvhn3nmjt3la5ltu
Parallel and Distributed Spatial Simulation of Chemical Reactions
2008
2008 22nd Workshop on Principles of Advanced and Distributed Simulation
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We describe an optimistic, parallel and distributed variant of the Next-Subvolume Method (NSM), a method that augments the well-known Gillespie Stochastic Simulation Algorithm (SSA) with spatial features ...
This holds true for large-scale cellbiological simulations, a field that has emerged as data and knowledge concerning these systems increases and biologists call for tools to guide wet-lab experimentation ...
Acknowledgments This research is partly supported by the DFG (German Research Foundation) and the DAAD. ...
doi:10.1109/pads.2008.20
dblp:conf/pads/JeschkePEFU08
fatcat:jzsqtvpytba2tkujfxd74cqq2q
Challenges of analysing stochastic gene expression in bacteria using single-cell time-lapse experiments
2021
Essays in Biochemistry
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In the present paper, the individual steps and challenges involved in a time-lapse experiment are discussed, and a rigorous framework for designing, performing, and extracting single-cell gene expression ...
Stochastic gene expression causes phenotypic heterogeneity in a population of genetically identical bacterial cells. ...
All figures included in the present paper are original and contain no third party material. ...
doi:10.1042/ebc20200015
pmid:33835126
pmcid:PMC8056041
fatcat:3dkxjpemp5dvfkluub4slb7zoy
Stochastic chemical kinetics
2013
Biophysical Reviews
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A review of the physical principles that are the ground of the stochastic formulation of chemical kinetics is presented along with a survey of the algorithms currently used to simulate it. ...
Advantages and limitations of the models are also discussed in the light of the more and more frequent use of these models and algorithms in modeling and simulating biochemical and even biological processes ...
Therefore, the algorithm cannot be easily adapted to simulate diffusion, localization, and spatial heterogeneity. ...
doi:10.1007/s12551-013-0122-2
pmid:28510113
pmcid:PMC5425731
fatcat:qmkdp4dgb5dnvdhwm5eywzn6iu
Communication-free and Parallel Simulation of Neutral Biodiversity Models
[article]
2021
arXiv
pre-print
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The GPU implementation further outperforms all algorithms on the CPU by a factor ranging from ∼ 2 to ∼ 80, depending on the model parameterisation and the analysis that is performed. ...
With our novel algorithm, a simulation can be (1) split up into independent batch jobs and (2) simulated across any number of heterogeneous machines - all without affecting the simulation result. ...
The algorithm works with a set of molecules that react with each other probabilistically. ...
arXiv:2108.05815v1
fatcat:tnqnti3s6vaqxpljdkttq2l3wu
FISIK: Framework for the Inference of in Situ Interaction Kinetics from single-molecule imaging data
[article]
2019
bioRxiv
pre-print
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We validated FISIK using a series of tests, where we simulated trajectories of diffusing molecules that interact with each other, considering a wide range of model parameters, and including resolution ...
We found that FISIK has the sensitivity to determine association and dissociation rates, where its accuracy depends on the labeled fraction of molecules and the extent of molecule tracking errors. ...
Inverting the Gillespie algorithm for the simulation of stochastic processes(36)
Figure 2 . 2 The intermediate statistics accurately reflect the modeled interactions. ...
doi:10.1101/530063
fatcat:blltkbsrfzbg3hjwp32tyxgl6i
Current Progress in Static and Dynamic Modeling of Biological Networks
[chapter]
2010
Systems Biology for Signaling Networks
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The relentless advance of biochemistry has enabled us to take apart biological systems with ever more fine-grained and precise instruments. ...
Given this broad outline of component connectivity, we may then attempt to reconstruct molecular physiology via dynamic modeling, computer simulations that model when cellular events occur (ODE), where ...
chemical kinetics framework (Gillespie 2007) . ...
doi:10.1007/978-1-4419-5797-9_2
fatcat:7pwcze2sbraszfcy5yacypur7e
Towards Human Cell Simulation
[chapter]
2019
Msphere
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., kinetic rates) are usually not available, a problem that hinders the execution of simulation algorithms as long as some parameter estimation methods are used. ...
Although mathematical models that describe the interactions among all biochemical processes in a cell are theoretically feasible, their simulation is generally hard because of a variety of reasons. ...
The authors RS and ZKO also acknowledges that work was supported by the Ministry of Education, Youth and ...
doi:10.1007/978-3-030-16272-6_8
fatcat:qpkryzcgpbec7nsgyndw5xpj7q
Simulation and inference algorithms for stochastic biochemical reaction networks: from basic concepts to state-of-the-art
2019
Journal of the Royal Society Interface
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Detailed algorithms for particularly important methods are described and complemented with Matlab® implementations. ...
As a result, this review provides a practical and accessible introduction to computational methods for stochastic models within the life sciences community. ...
The development of robust theory and algorithms accounting for spatial heterogeneity is still an active area of research [23, 28, 70] . ...
doi:10.1098/rsif.2018.0943
pmid:30958205
pmcid:PMC6408336
fatcat:btidqocrdrfftiwv3zwhhavxni
French Roadmap for complex Systems 2008-2009
[article]
2009
arXiv
pre-print
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and complexity science to the public, political and industrial spheres. ...
The aim of this roadmap is to foster the coordination of the complex systems community on focused topics and questions, as well as to present contributions and challenges in the complex systems sciences ...
The simulation algorithms (Gillespie algorithm) use the Delbrück-Bartholomay-Rényi representation of biochemical kinetics as jump Markov processes. ...
arXiv:0907.2221v1
fatcat:sfwycearbneirbi25t7dgta5py
A synthetic biology challenge: making cells compute
2007
Molecular Biosystems
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Advances in biology and engineering have enabled the reprogramming of cells with well-defined functions, leading to the emergence of synthetic biology. ...
We conclude with discussion of challenges involved in a typical design cycle, as well as those specific to cellular computation. ...
Acknowledgements We thank Mike West, John Pearson, and anonymous reviewers for critical reading of the manuscript and helpful discussions. ...
doi:10.1039/b618473c
pmid:17460793
fatcat:2pjk3znetzh65gi5tax65ln3qm
Partial differential equations for self-organization in cellular and developmental biology
2008
Nonlinearity
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, and the new modelling opportunities that are emerging as a result. ...
Understanding the mechanisms governing and regulating the emergence of structure and heterogeneity within cellular systems, such as the developing embryo, represents a multiscale challenge typifying current ...
The system may, however, be reinterpreted as a continuous time Markov chain and investigated using the Gillespie stochastic simulation algorithm (SSA) [120] . ...
doi:10.1088/0951-7715/21/11/r05
fatcat:e266xvcdfbcgxknyd2i54zshoq
Maps for when the living gets tough: Maneuvering through a hostile energy landscape
2016
IFAC-PapersOnLine
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To this end, we employ Gillespie algorithm-based methods (Gillespie, 2007) and a direct numerical solution of the chemical master equation (Kazeev et al., 2014) . ...
Towards that, systems biology, and especially metabolomics, allowed neuroscientists to move from the study of individual molecules or circuits to a systems-level perspective of the complexity of brain ...
doi:10.1016/j.ifacol.2017.03.002
fatcat:tmddfevk7ngd3p4wdpbq7xisb4
Modeling Self-Assembly Across Scales: The Unifying Perspective of Smart Minimal Particles
2011
Micromachines
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Our main claim is that the SMPs can be used to develop a unifying technological and methodological framework that bridges the gap between passive M/NEMS and active, centimeter-sized robots. ...
A wealth of current research in microengineering aims at fabricating devices of increasing complexity, notably by (self-)assembling elementary components into heterogeneous functional systems. ...
Acknowledgements Massimo Mastrangeli and Grégory Mermoud are sponsored by the SelfSys project funded by the Swiss research initiative Nano-Tera.ch. ...
doi:10.3390/mi2020082
fatcat:lgwr25lft5d7hopkd3y37q4ubu
Stochasticity in the miR-9/Hes1 oscillatory network can account for clonal heterogeneity in the timing of differentiation
2016
eLife
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Surprisingly, inherent stochasticity also increases the robustness of the progenitor state and lessens the impact of unequal, random distribution of molecules at cell division on the temporal spread of ...
We report that increased stochasticity spreads the timing of differentiation in a population, such that initially equivalent cells differentiate over a period of time. ...
Author contributions NEP, CSM, TP, VB, EM, NP, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article; PS, MR, Conception and design, Acquisition ...
doi:10.7554/elife.16118
pmid:27700985
pmcid:PMC5050025
fatcat:dbjcdstnwzey7dfskeo4ymkcja
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