Warning: Undefined array key "mm" in /www/wwwroot/www.ai-bt.com/si.php on line 10 Deprecated: trim(): Passing null to parameter #1 ($string) of type string is deprecated in /www/wwwroot/www.ai-bt.com/si.php on line 10 GillesPy: A Python Package for Stochastic Model Building and Simulation.

Literature DB >> 28630888

GillesPy: A Python Package for Stochastic Model Building and Simulation.

John H Abel¹, Brian Drawert², Andreas Hellander³, Linda R Petzold².

Abstract

GillesPy is an open-source Python package for model construction and simulation of stochastic biochemical systems. GillesPy consists of a Python framework for model building and an interface to the StochKit2 suite of efficient simulation algorithms based on the Gillespie stochastic simulation algorithms (SSA). To enable intuitive model construction and seamless integration into the scientific Python stack, we present an easy to understand, action-oriented programming interface. Here, we describe the components of this package and provide a detailed example relevant to the computational biology community.

Keywords: Biological systems; open-source software; stochastic systems; systems biology

Year: 2016 PMID： 28630888 PMCID： PMC5473341 DOI： 10.1109/LLS.2017.2652448

Source DB: PubMed Journal: IEEE Life Sci Lett

15 in total

1. Construction of a genetic toggle switch in Escherichia coli.

Authors: T S Gardner; C R Cantor; J J Collins
Journal: Nature Date: 2000-01-20 Impact factor: 49.962

2. Stochastic gene expression in a single cell.

Authors: Michael B Elowitz; Arnold J Levine; Eric D Siggia; Peter S Swain
Journal: Science Date: 2002-08-16 Impact factor: 47.728

3. Adaptive explicit-implicit tau-leaping method with automatic tau selection.

Authors: Yang Cao; Daniel T Gillespie; Linda R Petzold
Journal: J Chem Phys Date: 2007-06-14 Impact factor: 3.488

4. MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME.

Authors: Brian Drawert; Michael Trogdon; Salman Toor; Linda Petzold; Andreas Hellander
Journal: SIAM J Sci Comput Date: 2016-06-01 Impact factor: 2.373

5. A constant-time kinetic Monte Carlo algorithm for simulation of large biochemical reaction networks.

Authors: Alexander Slepoy; Aidan P Thompson; Steven J Plimpton
Journal: J Chem Phys Date: 2008-05-28 Impact factor: 3.488

6. Noise-induced breakdown of the Michaelis-Menten equation in steady-state conditions.

Authors: R Grima
Journal: Phys Rev Lett Date: 2009-05-29 Impact factor: 9.161

7. StochKit2: software for discrete stochastic simulation of biochemical systems with events.

Authors: Kevin R Sanft; Sheng Wu; Min Roh; Jin Fu; Rone Kwei Lim; Linda R Petzold
Journal: Bioinformatics Date: 2011-07-04 Impact factor: 6.937

8. Accuracy of the Michaelis-Menten approximation when analysing effects of molecular noise.

Authors: Michael J Lawson; Linda Petzold; Andreas Hellander
Journal: J R Soc Interface Date: 2015-05-06 Impact factor: 4.118

9. Perspective: Stochastic algorithms for chemical kinetics.

Authors: Daniel T Gillespie; Andreas Hellander; Linda R Petzold
Journal: J Chem Phys Date: 2013-05-07 Impact factor: 3.488

10. Spatial stochastic dynamics enable robust cell polarization.

Authors: Michael J Lawson; Brian Drawert; Mustafa Khammash; Linda Petzold; Tau-Mu Yi
Journal: PLoS Comput Biol Date: 2013-07-25 Impact factor: 4.475

9 in total

1. Smart computational exploration of stochastic gene regulatory network models using human-in-the-loop semi-supervised learning.

Authors: Fredrik Wrede; Andreas Hellander
Journal: Bioinformatics Date: 2019-12-15 Impact factor: 6.937

GillesPy: A Python Package for Stochastic Model Building and Simulation.

1. Construction of a genetic toggle switch in Escherichia coli.

2. Stochastic gene expression in a single cell.

3. Adaptive explicit-implicit tau-leaping method with automatic tau selection.

4. MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME.

5. A constant-time kinetic Monte Carlo algorithm for simulation of large biochemical reaction networks.

6. Noise-induced breakdown of the Michaelis-Menten equation in steady-state conditions.

7. StochKit2: software for discrete stochastic simulation of biochemical systems with events.

8. Accuracy of the Michaelis-Menten approximation when analysing effects of molecular noise.

9. Perspective: Stochastic algorithms for chemical kinetics.

10. Spatial stochastic dynamics enable robust cell polarization.

1. Smart computational exploration of stochastic gene regulatory network models using human-in-the-loop semi-supervised learning.

2. Comparison of solitary and collective foraging strategies of Caenorhabditis elegans in patchy food distributions.

3. Multiscale Modelling Tool: Mathematical modelling of collective behaviour without the maths.

Review 4. Beyond Deterministic Models in Drug Discovery and Development.

5. Epidemiological modeling in StochSS Live!

6. BioSANS: A software package for symbolic and numeric biological simulation.

7. Cheater suppression and stochastic clearance through quorum sensing.

8. Estimating the transfer rates of bacterial plasmids with an adapted Luria-Delbrück fluctuation analysis.

9. A multiscale compartment-based model of stochastic gene regulatory networks using hitting-time analysis.