list of systems biology modeling software

Systems biology relies heavily on building mathematical models to help understand and make predictions of biological processes. Specialized software to assist in building models has been developed since the arrival of the first digital computers.{{cite journal |last1=Chance |first1=Britton |last2=Garfinkel |first2=David |last3=Higgins |first3=Joseph |last4=Hess |first4=Benno |last5=Chance |first5=E.M. |title=Metabolic Control Mechanisms |journal=Journal of Biological Chemistry |date=August 1960 |volume=235 |issue=8 |pages=2426–2439 |doi=10.1016/S0021-9258(18)64638-1|doi-access=free }}{{cite book |last1=Chance |first1=Britton |last2=Higgins |first2=Joseph |last3=Garfinkel |first3=David |title=Analogue and digital computer representations of biochemical processes |date=1962 |publisher=Federation Proceedings, Vol 12. No. 1-2 |location=Federation of American Societies for Experimental Biology.. |pages=75}}{{cite thesis |last1=Burns |first1=Jim |title=Metabolic Control Analysis |journal=Thesis |date=1 March 1973 |doi=10.5281/zenodo.7240738}}{{cite journal |last1=Garfinkel |first1=David |title=A machine-independent language for the simulation of complex chemical and biochemical systems |journal=Computers and Biomedical Research |date=August 1968 |volume=2 |issue=1 |pages=31–44 |doi=10.1016/0010-4809(68)90006-2|pmid=5743538 }} The following list gives the currently supported software applications available to researchers.

The vast majority of modern systems biology modeling software support SBML, which is the de facto standard for exchanging models of biological cellular processes. Some tools also support CellML, a standard used for representing physiological processes. The advantage of using standard formats is that even though a particular software application may eventually become unsupported and even unusable, the models developed by that application can be easily transferred to more modern equivalents. This allows scientific research to be reproducible long after the original publication of the work.

To obtain more information about a particular tool, click on the name of the tool. This will direct you either to a peer-reviewed publication or, in some rare cases, to a dedicated Wikipedia page.

Actively supported open-source software applications

= General information =

When an entry in the SBML column states "Yes, but only for reactions.", it means that the tool only supports the reaction component of SBML. For example, rules, events, etc. are not supported.

class="wikitable" ! Name ! Description/Notability	OS	License	Site	SBML Support
[https://pubmed.ncbi.nlm.nih.gov/29944839/ iBioSim] \| iBioSim{{cite journal \|last1=Watanabe \|first1=Leandro \|last2=Nguyen \|first2=Tramy \|last3=Zhang \|first3=Michael \|last4=Zundel \|first4=Zach \|last5=Zhang \|first5=Zhen \|last6=Madsen \|first6=Curtis \|last7=Roehner \|first7=Nicholas \|last8=Myers \|first8=Chris \|title=iBioSim3: A Tool for Model-Based Genetic Circuit Design \|journal=ACS Synthetic Biology \|date=19 July 2019 \|volume=8 \|issue=7 \|pages=1560–1563 \|doi=10.1021/acssynbio.8b00078\|pmid=29944839 \|s2cid=49429947 }}{{cite journal \|last1=Martínez-García \|first1=Esteban \|last2=Goñi-Moreno \|first2=Angel \|last3=Bartley \|first3=Bryan \|last4=McLaughlin \|first4=James \|last5=Sánchez-Sampedro \|first5=Lucas \|last6=Pascual del Pozo \|first6=Héctor \|last7=Prieto Hernández \|first7=Clara \|last8=Marletta \|first8=Ada Serena \|last9=De Lucrezia \|first9=Davide \|last10=Sánchez-Fernández \|first10=Guzmán \|last11=Fraile \|first11=Sofía \|last12=de Lorenzo \|first12=Víctor \|title=SEVA 3.0: an update of the Standard European Vector Architecture for enabling portability of genetic constructs among diverse bacterial hosts \|journal=Nucleic Acids Research \|date=8 January 2020 \|volume=48 \|issue=D1 \|pages=D1164–D1170 \|doi=10.1093/nar/gkz1024\|pmid=31740968 \|pmc=7018797 }} is a computer-aided design (CAD) tool for the modeling, analysis, and design of genetic circuits.	multiplatform (Java/C++)	Apache License	[https://github.com/MyersResearchGroup/iBioSim]	Yes
CompuCell3D \| GUI/Scripting tool{{cite book \|last1=Swat \|first1=Maciej H. \|last2=Thomas \|first2=Gilberto L. \|last3=Belmonte \|first3=Julio M. \|last4=Shirinifard \|first4=Abbas \|last5=Hmeljak \|first5=Dimitrij \|last6=Glazier \|first6=James A. \|title=Computational Methods in Cell Biology \|chapter=Multi-Scale Modeling of Tissues Using CompuCell3D \|date=2012 \|volume=110 \|pages=325–366 \|doi=10.1016/B978-0-12-388403-9.00013-8\|pmid=22482955 \|pmc=3612985 \|isbn=9780123884039 }} for building and simulating multicellular models.	multiplatform (C++/Python)	MIT	[https://compucell3d.org/]	Yes, but only for reactions.
COPASI \| GUI tool{{cite journal \|last1=Bergmann \|first1=Frank T. \|last2=Hoops \|first2=Stefan \|last3=Klahn \|first3=Brian \|last4=Kummer \|first4=Ursula \|last5=Mendes \|first5=Pedro \|last6=Pahle \|first6=Jürgen \|last7=Sahle \|first7=Sven \|title=COPASI and its applications in biotechnology \|journal=Journal of Biotechnology \|date=November 2017 \|volume=261 \|pages=215–220 \|doi=10.1016/j.jbiotec.2017.06.1200\|pmid=28655634 \|pmc=5623632 }}{{cite journal \|last1=Yeoh \|first1=Jing Wui \|last2=Ng \|first2=Kai Boon Ivan \|last3=Teh \|first3=Ai Ying \|last4=Zhang \|first4=JingYun \|last5=Chee \|first5=Wai Kit David \|last6=Poh \|first6=Chueh Loo \|title=An Automated Biomodel Selection System (BMSS) for Gene Circuit Designs \|journal=ACS Synthetic Biology \|date=19 July 2019 \|volume=8 \|issue=7 \|pages=1484–1497 \|doi=10.1021/acssynbio.8b00523\|pmid=31035759 \|s2cid=140321282 }} for analyzing and simulating SBML models.	multiplatform (C++)	Artistic License	[http://www.copasi.org]	Yes
[https://pubmed.ncbi.nlm.nih.gov/17855418/ Cytosim]	Spatial simulator for flexible cytoskeletal filaments and motor proteins{{cite journal \|last1=Nedelec \|first1=Francois \|last2=Foethke \|first2=Dietrich \|title=Collective Langevin dynamics of flexible cytoskeletal fibers \|journal=New Journal of Physics \|volume=9 \|date=2007 \|issue=11 \|pages=427\|doi=10.1088/1367-2630/9/11/427 \|arxiv=0903.5178 \|bibcode=2007NJPh....9..427N \|s2cid=16924457 }}	Mac, Linux, Cygwin (C++)	GPL3	[http://cytosim.org]	Not applicable
[https://pubmed.ncbi.nlm.nih.gov/26085503/ libroadrunner] \| High-performance software library for simulation and analysis of SBML models{{cite journal \|last1=Somogyi \|first1=Endre T. \|last2=Bouteiller \|first2=Jean-Marie \|last3=Glazier \|first3=James A. \|last4=König \|first4=Matthias \|last5=Medley \|first5=J. Kyle \|last6=Swat \|first6=Maciej H. \|last7=Sauro \|first7=Herbert M. \|title=libRoadRunner: a high performance SBML simulation and analysis library: Table 1. \|journal=Bioinformatics \|date=15 October 2015 \|volume=31 \|issue=20 \|pages=3315–3321 \|doi=10.1093/bioinformatics/btv363\|pmid=26085503 \|pmc=4607739 }}{{cite journal \|last1=Ghaffarizadeh \|first1=Ahmadreza \|last2=Heiland \|first2=Randy \|last3=Friedman \|first3=Samuel H. \|last4=Mumenthaler \|first4=Shannon M. \|last5=Macklin \|first5=Paul \|title=PhysiCell: An open source physics-based cell simulator for 3-D multicellular systems \|journal=PLOS Computational Biology \|date=23 February 2018 \|volume=14 \|issue=2 \|pages=e1005991 \|doi=10.1371/journal.pcbi.1005991\|pmid=29474446 \|pmc=5841829 \|bibcode=2018PLSCB..14E5991G \|doi-access=free }}	multiplatform (C/C++)	Apache License	[https://github.com/sys-bio/roadrunner]	Yes
[https://pubmed.ncbi.nlm.nih.gov/33507922/ massPy] \| Simulation tool {{cite journal \|last1=Haiman \|first1=Zachary B. \|last2=Zielinski \|first2=Daniel C. \|last3=Koike \|first3=Yuko \|last4=Yurkovich \|first4=James T. \|last5=Palsson \|first5=Bernhard O. \|title=MASSpy: Building, simulating, and visualizing dynamic biological models in Python using mass action kinetics \|journal=PLOS Computational Biology \|date=28 January 2021 \|volume=17 \|issue=1 \|pages=e1008208 \|doi=10.1371/journal.pcbi.1008208\|pmid=33507922 \|pmc=7872247 \|bibcode=2021PLSCB..17E8208H \|doi-access=free }}{{cite journal \|last1=Foster \|first1=Charles J \|last2=Wang \|first2=Lin \|last3=Dinh \|first3=Hoang V \|last4=Suthers \|first4=Patrick F \|last5=Maranas \|first5=Costas D \|title=Building kinetic models for metabolic engineering \|journal=Current Opinion in Biotechnology \|date=February 2021 \|volume=67 \|pages=35–41 \|doi=10.1016/j.copbio.2020.11.010\|pmid=33360621 \|s2cid=229690954 }} that can work with COBRApy{{cite journal \|last1=Ebrahim \|first1=Ali \|last2=Lerman \|first2=Joshua A \|last3=Palsson \|first3=Bernhard O \|last4=Hyduke \|first4=Daniel R \|title=COBRApy: COnstraints-Based Reconstruction and Analysis for Python \|journal=BMC Systems Biology \|date=December 2013 \|volume=7 \|issue=1 \|pages=74 \|doi=10.1186/1752-0509-7-74\|pmid=23927696 \|pmc=3751080 \|doi-access=free }}	multiplatform (Python)	MIT	[https://github.com/SBRG/MASSpy]	Yes
[https://pubmed.ncbi.nlm.nih.gov/30945248/ MCell] \| GUI tool for particle-based spatial stochastic simulation with individual molecules{{cite journal \|last1=Stiles \|first1=Joel R. \|last2=Van Helden \|first2=Dirk \|last3=Bartol \|first3=Thomas M. \|last4=Salpeter \|first4=Edwin E. \|last5=Salpeter \|first5=Miriam M \|title=Miniature endplate current rise times <100 us from improved dual recordings can be modeled with passive acetylcholine diffusion from a synaptic vesicle \|journal=Proc. Natl. Acad. Sci. USA \|date=1996 \|volume=93 \|issue=12 \|pages=5747–5752\|doi=10.1073/pnas.93.12.5747 \|pmid=8650164 \|pmc=39132 \|doi-access=free }}{{cite journal \|last1=Stiles \|first1=Joel R. \|last2=Bartol \|first2=Thomas M. \|title=Monte Carlo methods for simulating realistic synaptic microphysiology using MCell \|date=2001 \|journal=Computational Neuroscience: Realistic Modeling for Experimentalists \|pages=87–127}}{{cite journal \|last1=Kerr \|first1=R \|last2=Bartol \|first2=TM \|last3=Kaminsky \|first3=B \|last4=Dittrich \|first4=M \|last5=Chang \|first5=JCJ \|last6=Baden \|first6=S \|last7=Sejnowski \|first7=TJ \|last8=Stiles \|first8=JR \|title=Fast Monte Carlo simulation methods for biological reaction-diffusion systems in solution and on surfaces \|date=2008 \|journal=SIAM J. Sci. Comput. \|volume=30 \|issue=6 \|pages=3126–3149\|doi=10.1137/070692017 \|pmid=20151023 \|pmc=2819163 \|bibcode=2008SJSC...30.3126K }}	multiplatform	MIT and GPLv2	[https://mcell.org/index.html]	Not applicable
[https://opencor.ws/ OpenCOR] \|A cross-platform modelling environment, which is aimed at organizing, editing, simulating, and analysing CellML files on Windows, Linux and macOS. \|multiplatform (C++/Python) \|GPLv3 \|[https://opencor.ws/] \|Uses CellML
[https://pubmed.ncbi.nlm.nih.gov/30169736/ PhysiBoSS] \| A specialized form of the PhysiCell agent-based modeling platform that directly integrates Boolean signaling networks into cell Agents{{cite journal \|last1=Letort \|first1=Gaelle \|last2=Montagud \|first2=Arnau \|last3=Stoll \|first3=Gautier \|last4=Heiland \|first4=Randy \|last5=Barillot \|first5=Emmanuel \|last6=Macklin \|first6=Paul \|last7=Zinovyev \|first7=Andrei \|last8=Calzone \|first8=Laurence \|title=PhysiBoSS: a multi-scale agent-based modelling framework integrating physical dimension and cell signalling \|journal=Bioinformatics \|date=1 April 2019 \|volume=35 \|issue=7 \|pages=1188–1196 \|doi=10.1093/bioinformatics/bty766\|pmid=30169736 \|pmc=6449758 }}	multiplatform (C++)	BSD-3	[https://github.com/PhysiBoSS/PhysiBoSS]	Yes, but only for reactions
[https://pubmed.ncbi.nlm.nih.gov/29474446/ PhysiCell] \| A agent-based{{cite journal \|last1=Ghaffarizadeh \|first1=Ahmadreza \|last2=Heiland \|first2=Randy \|last3=Friedman \|first3=Samuel H. \|last4=Mumenthaler \|first4=Shannon M. \|last5=Macklin \|first5=Paul \|title=PhysiCell: An open source physics-based cell simulator for 3-D multicellular systems \|journal=PLOS Computational Biology \|date=23 February 2018 \|volume=14 \|issue=2 \|pages=e1005991 \|doi=10.1371/journal.pcbi.1005991\|pmid=29474446 \|pmc=5841829 \|bibcode=2018PLSCB..14E5991G \|doi-access=free }} modeling framework for multicellular systems biology.	multiplatform (C++)	BSD-3	[http://physicell.org]	Yes, but only for reactions
[https://pubmed.ncbi.nlm.nih.gov/15454409/ PySCeS] \| Python tool for modeling and analyzing SBML models{{cite journal \|last1=Olivier \|first1=B. G. \|last2=Rohwer \|first2=J. M. \|last3=Hofmeyr \|first3=J.-H. S. \|title=Modelling cellular systems with PySCeS \|journal=Bioinformatics \|date=15 February 2005 \|volume=21 \|issue=4 \|pages=560–561 \|doi=10.1093/bioinformatics/bti046\|pmid=15454409 \|doi-access=free }}{{cite journal \|last1=Mendoza-Cózatl \|first1=David G. \|last2=Moreno-Sánchez \|first2=Rafael \|title=Control of glutathione and phytochelatin synthesis under cadmium stress. Pathway modeling for plants \|journal=Journal of Theoretical Biology \|date=February 2006 \|volume=238 \|issue=4 \|pages=919–936 \|doi=10.1016/j.jtbi.2005.07.003\|pmid=16125728 \|bibcode=2006JThBi.238..919M }}{{cite journal \|last1=Ghaffarizadeh \|first1=Ahmadreza \|last2=Heiland \|first2=Randy \|last3=Friedman \|first3=Samuel H. \|last4=Mumenthaler \|first4=Shannon M. \|last5=Macklin \|first5=Paul \|title=PhysiCell: An open source physics-based cell simulator for 3-D multicellular systems \|journal=PLOS Computational Biology \|date=23 February 2018 \|volume=14 \|issue=2 \|pages=e1005991 \|doi=10.1371/journal.pcbi.1005991\|pmid=29474446 \|pmc=5841829 \|bibcode=2018PLSCB..14E5991G \|doi-access=free }}	multiplatform (Python)	BSD-3	[https://pysces.sourceforge.net/]	Yes
[https://pubmed.ncbi.nlm.nih.gov/23423320/ pySB] \| Python-based{{cite journal \|last1=Stefan \|first1=Melanie I. \|last2=Bartol \|first2=Thomas M. \|last3=Sejnowski \|first3=Terrence J. \|last4=Kennedy \|first4=Mary B. \|title=Multi-state Modeling of Biomolecules \|journal=PLOS Computational Biology \|date=25 September 2014 \|volume=10 \|issue=9 \|pages=e1003844 \|doi=10.1371/journal.pcbi.1003844\|pmid=25254957 \|pmc=4201162 \|bibcode=2014PLSCB..10E3844S \|doi-access=free }} platform with specialization in rule-based models.	multiplatform (Python)	BSD-3	[https://pysb.org/]	Partial
[https://pubmed.ncbi.nlm.nih.gov/30818351/ ReaDDy] \| Particle-based spatial simulator with intermolecular potentials{{cite journal \|last1=Schöneberg \|first1=J. \|last2=Ullrich \|first2=A. \|last3=Noé \|first3=F. \|date=2014 \|title=Simulation tools for particle-based reaction-diffusion dynamics in continuous space \|journal=BMC Biophys. \|volume=7 \|page=11 \|doi=10.1186/s13628-014-0011-5 \|pmid=25737778 \|pmc=4347613 \|doi-access=free }}	Linux and Mac	Custom	[https://readdy.github.io/index.html]	Not applicable
[https://pubmed.ncbi.nlm.nih.gov/34554191/ SBSCL] \| Java library{{cite journal \|last1=Panchiwala \|first1=H \|last2=Shah \|first2=S \|last3=Planatscher \|first3=H \|last4=Zakharchuk \|first4=M \|last5=König \|first5=M \|last6=Dräger \|first6=A \|title=The Systems Biology Simulation Core Library. \|journal=Bioinformatics \|date=23 September 2021 \|volume=38 \|issue=3 \|pages=864–865 \|doi=10.1093/bioinformatics/btab669 \|pmid=34554191\|pmc=8756180 }}{{cite journal \|last1=Tangherloni \|first1=Andrea \|last2=Nobile \|first2=Marco S. \|last3=Cazzaniga \|first3=Paolo \|last4=Capitoli \|first4=Giulia \|last5=Spolaor \|first5=Simone \|last6=Rundo \|first6=Leonardo \|last7=Mauri \|first7=Giancarlo \|last8=Besozzi \|first8=Daniela \|title=FiCoS: A fine-grained and coarse-grained GPU-powered deterministic simulator for biochemical networks \|journal=PLOS Computational Biology \|date=9 September 2021 \|volume=17 \|issue=9 \|pages=e1009410 \|doi=10.1371/journal.pcbi.1009410\|pmid=34499658 \|pmc=8476010 \|bibcode=2021PLSCB..17E9410T \|doi-access=free }} with efficient and exhaustive support for SBML	multiplatform (Java)	LGPL	[https://draeger-lab.github.io/SBSCL/]	Yes
[https://pubmed.ncbi.nlm.nih.gov/14683609/ SBW (software)] \| A distributed workbench{{cite journal \|last1=Hucka \|first1=M. \|last2=Finney \|first2=A. \|last3=Sauro \|first3=H. M. \|last4=Bolouri \|first4=H. \|last5=Doyle \|first5=J. \|last6=Kitano \|first6=H. \|title=The Erato Systems Biology Workbench: Enabling Interaction and Exchange Between Software Tools for Computational Biology \|journal=Biocomputing 2002 \|date=December 2001 \|pages=450–461 \|doi=10.1142/9789812799623_0042\|pmid=11928498 \|isbn=978-981-02-4777-5 \|url=https://resolver.caltech.edu/CaltechAUTHORS:20130108-142104885 \|hdl=2299/11944 \|hdl-access=free }}{{cite journal \|last1=Kawasaki \|first1=Regiane \|last2=Baraúna \|first2=Rafael A. \|last3=Silva \|first3=Artur \|last4=Carepo \|first4=Marta S. P. \|last5=Oliveira \|first5=Rui \|last6=Marques \|first6=Rodolfo \|last7=Ramos \|first7=Rommel T. J. \|last8=Schneider \|first8=Maria P. C. \|title=Reconstruction of the Fatty Acid Biosynthetic Pathway of Exiguobacterium antarcticum B7 Based on Genomic and Bibliomic Data \|journal=BioMed Research International \|date=2016 \|volume=2016 \|pages=1–9 \|doi=10.1155/2016/7863706\|pmid=27595107 \|pmc=4993939 \|doi-access=free }} that includes many modeling tools	multiplatform (C/C++)	BSD-3	[https://sbw.sourceforge.net/]	Yes
Smoldyn \| Particle-based simulator for spatial stochastic simulations with individual molecules{{cite journal \|last1=Andrews \|first1=Steven S. \|last2=Bray \|first2=Dennis \|title=Stochastic simulation of chemical reactions with spatial resolution and single molecule detail \|journal=Physical Biology \|date=2004 \|volume=1 \|issue=3–4 \|pages=137–151\|doi=10.1088/1478-3967/1/3/001 \|pmid=16204833 \|bibcode=2004PhBio...1..137A \|s2cid=16394428 }}{{cite journal \|last1=Andrews \|first1=Steven S. \|last2=Addy \|first2= Nathan J. \|last3= Brent \|first3=Roger \|last4=Arkin \|first4=Adam P. \|title=Detailed simulations of cell biology with Smoldyn 2.1 \|journal=PLOS Comput. Biol. \|date=2010 \|volume=6 \|issue=3 \|pages=e1000705\|doi=10.1371/journal.pcbi.1000705 \|pmid=20300644 \|pmc=2837389 \|bibcode=2010PLSCB...6E0705A \|doi-access=free }}{{cite journal \|last1=Andrews \|first1=Steven S. \|title=Smoldyn: particle-based simulation with rule-based modeling, improved molecular interaction, and a library interface \|journal=Bioinformatics \|date=2017 \|volume=33 \|issue=5 \|pages=710–717\|doi=10.1093/bioinformatics/btw700 \|pmid=28365760 \|doi-access=free }}{{cite journal \|last1=Singh \|first1 =Dilawar \|last2=Andrews \|first2=Steven S. \|title=Python interfaces for the Smoldyn simulator \|journal=Bioinformatics \|date=2022 \|volume=38 \|issue =1 \|pages=291–293\|doi =10.1093/bioinformatics/btab530 \|pmid =34293100 }}	multiplatform (C/C++/Python)	LGPL	[https://www.smoldyn.org/]	Not applicable
[https://pubmed.ncbi.nlm.nih.gov/28451982/ Spatiocyte] \| Spatial modeling software that uses a fine lattice with up to one molecule per site{{cite book \|last1=Arjunan \|first1=S.N.V. \|last2= Takahashi \|first2= K. \|date=2017 \|title=Multi-algorithm particle simulations with Spatiocyte \|series=Methods in Molecular Biology \|volume=1611 \|pages=219–236}}{{cite journal \|last1=Arjunan \|first1=S.N.V. \|last2= Miyauchi \|first2=A. \|last3=Iwamoto \|first3= K. \|last4=Takahashi \|first4=K. \|date=2020 \|title=pSpatiocyte: a high-performance simulator for intracellular reaction-diffusion systems \|journal=BMC Bioinformatics \|volume=21 \|issue=1 \|pages=33\|doi=10.1186/s12859-019-3338-8 \|pmid=31996129 \|pmc=6990473 \|doi-access=free }}	multiplatform	Unknown	[https://spatiocyte.org]	Not applicable
[https://pubmed.ncbi.nlm.nih.gov/26840718/ SpringSaLaD] \| Particle-based spatial simulator in which molecules are spheres that are linked by springs{{cite journal \|last1=Michalski \|first1=P.J. \|last2=Loew \|first2=L.M. \|date=2016 \|title=SpringSaLaD: a spatial, particle-based biochemical simulation platform with excluded volume \|journal=Biophys. J. \|volume=110 \|issue=3 \|pages=523–529\|doi=10.1016/j.bpj.2015.12.026 \|pmid=26840718 \|pmc=4744174 \|bibcode=2016BpJ...110..523M }}	multiplatform	Unknown	[https://vcell.org/ssalad]	Not applicable
[https://pubmed.ncbi.nlm.nih.gov/22574658/ STEPS] \|Stochastic reaction-diffusion and membrane potential solver on distributed meshes{{cite journal \|last1=Hepburn \|first1=Iain \|last2=Chen \|first2=Weiliang \|last3=Wils \|first3=Stefan \|last4=De Schutter \|first4=Erik \|title=STEPS: efficient simulation of stochastic reaction–diffusion models in realistic morphologies \|journal=BMC Systems Biology \|date=May 2012 \|volume=7 \|issue=1 \|pages=36 \|doi=10.1186/1752-0509-6-36\|pmid=22574658 \|pmc=3472240 \|s2cid=9165862 \|doi-access=free }}{{cite journal \|last1=Chen \|first1=Weiliang \|last2=De Schutter \|first2=Erik \|title=Parallel STEPS: Large Scale Stochastic Spatial Reaction-Diffusion Simulation with High Performance Computers \|journal=Frontiers in Neuroinformatics \|date=February 2017 \|volume=11 \|issue=1 \|pages=13 \|doi=10.3389/fninf.2017.00013\|pmid=28239346 \|pmc=5301017 \|doi-access=free }}{{cite journal \|last1=Hepburn \|first1=Iain \|last2=Chen \|first2=Weiliang \|last3=De Schutter \|first3=Erik \|title=Accurate reaction-diffusion operator splitting on tetrahedral meshes for parallel stochastic molecular simulations \|journal=The Journal of Chemical Physics \|date=August 2016 \|volume=145 \|issue=5 \|pages=054118 \|doi=10.1063/1.4960034\|pmid=27497550 \|arxiv=1512.03126 \|bibcode=2016JChPh.145e4118H \|s2cid=17356298 }}{{cite journal \|last1=Chen \|first1=Weiliang \|last2=Carel \|first2=Tristan \|last3=Awile \|first3=Omar \|last4=Cantarutti \|first4=Nicola \|last5=Castiglioni \|first5=Giacomo \|last6=Cattabiani \|first6=Alessandro \|last7=Del Marmol \|first7=Baudouin \|last8=Hepburn \|first8=Iain \|last9=King \|first9=James G. \|last10=Kotsalos \|first10=Christos \|last11=Kumbhar \|first11=Pramod \|last12=Lallouette \|first12=Jules \|last13=Melchior \|first13=Samuel \|last14=Schürmann \|first14=Felix \|last15=De Schutter \|first15=Erik \|title=STEPS 4.0: Fast and memory-efficient molecular simulations of neurons at the nanoscale \|journal=Frontiers in Neuroinformatics \|date=October 2022 \|volume=16 \|page=883742 \|doi=10.3389/fninf.2022.883742 \|pmid=36387588 \|pmc=9645802 \|issn=1662-5196\|doi-access=free }} \|multiplatform (C++/Python) \|GPLv2 \|[https://steps.sourceforge.net] \|Partial [https://steps.sourceforge.net/manual/sbml_importer.html#Level-of-support]
[https://pubmed.ncbi.nlm.nih.gov/30053414/ Tellurium (software)] \| Simulation environment,{{cite journal \|last1=Choi \|first1=Kiri \|last2=Medley \|first2=J. Kyle \|last3=König \|first3=Matthias \|last4=Stocking \|first4=Kaylene \|last5=Smith \|first5=Lucian \|last6=Gu \|first6=Stanley \|last7=Sauro \|first7=Herbert M. \|title=Tellurium: An extensible python-based modeling environment for systems and synthetic biology \|journal=Biosystems \|date=September 2018 \|volume=171 \|pages=74–79 \|doi=10.1016/j.biosystems.2018.07.006\|pmid=30053414 \|pmc=6108935 }}{{cite journal \|last1=Pease \|first1=Nicholas A. \|last2=Nguyen \|first2=Phuc H.B. \|last3=Woodworth \|first3=Marcus A. \|last4=Ng \|first4=Kenneth K.H. \|last5=Irwin \|first5=Blythe \|last6=Vaughan \|first6=Joshua C. \|last7=Kueh \|first7=Hao Yuan \|title=Tunable, division-independent control of gene activation timing by a polycomb switch \|journal=Cell Reports \|date=March 2021 \|volume=34 \|issue=12 \|pages=108888 \|doi=10.1016/j.celrep.2021.108888\|pmid=33761349 \|pmc=8024876 }} that packages multiple libraries into one platform.	multiplatform (Python)	Apache License	[https://github.com/sys-bio/tellurium]	Yes
[https://pubmed.ncbi.nlm.nih.gov/22727185/ URDME] \| Stochastic reaction-diffusion simulation on unstructured meshes{{cite journal \|last1=Drawert \|first1=B. \|last2=Engblom \|first2=S. \|last3=Hellander \|first3=A \|title=URDME: A modular framework for stochastic simulation of reaction-transport processes in complex geometries \|journal=BMC Systems Biology \|volume=6 \|date=2012\|page=76 \|doi=10.1186/1752-0509-6-76 \|pmid=22727185 \|pmc=3439286 \|doi-access=free }}	MatLab on Mac, Linux	GPL3	[http://urdme.github.io/urdme/]	Not applicable
VCell \| Comprehensive modeling platform{{cite journal \|last1=Schaff \|first1=J. \|last2=Fink \|first2=C.C. \|last3=Slepchenko \|first3=B. \|last4=Carson \|first4=J.H. \|last5=Loew \|first5=L.M. \|title=A general computational framework for modeling cellular structure and function \|journal=Biophysical Journal \|date=September 1997 \|volume=73 \|issue=3 \|pages=1135–1146 \|doi=10.1016/S0006-3495(97)78146-3\|pmid=9284281 \|pmc=1181013 \|bibcode=1997BpJ....73.1135S \|s2cid=39818739 }}{{cite book \|last1=Cowan \|first1=Ann E. \|last2=Moraru \|first2=Ion I. \|last3=Schaff \|first3=James C. \|last4=Slepchenko \|first4=Boris M. \|last5=Loew \|first5=Leslie M. \|title=Computational Methods in Cell Biology \|chapter=Spatial Modeling of Cell Signaling Networks \|date=2012 \|volume=110 \|pages=195–221 \|doi=10.1016/B978-0-12-388403-9.00008-4\|pmid=22482950 \|pmc=3519356 \|isbn=9780123884039 }} for non-spatial, spatial, deterministic and stochastic simulations, including both reaction networks and reaction rules.	multiplatform (Java)	MIT	[https://vcell.org]	Yes

Specialist Tools

The following table lists specialist tools that cannot be grouped with the modeling tools.

class="wikitable"

! Name

! Description/Notability

License

Site

[https://academic.oup.com/bioinformatics/article/34/1/124/4158030 PySCeSToolbox]

| PySCeSToolbox{{cite journal |last1=Christensen |first1=Carl D |last2=Hofmeyr |first2=Jan-Hendrik S |last3=Rohwer |first3=Johann M |title=PySCeSToolbox: a collection of metabolic pathway analysis tools |journal=Bioinformatics |date=1 January 2018 |volume=34 |issue=1 |pages=124–125 |doi=10.1093/bioinformatics/btx567|pmid=28968872 |doi-access=free }} is a set of metabolic model analysis tools. Among other features, it can be used to generate the control analysis equations that relate the elasticities to the control coefficients. The package is cross-platform and requires PySCeS and Maxima to operate.

multiplatform (C++/Python)

BSD-3

[https://github.com/PySCeS/PyscesToolbox]

Feature Tables

= Supported modeling paradigms =

class="wikitable" ! Name	ODE	Constraint based	Stochastic	Logical	Agent based	Spatial (particle)	Spatial (continuous)
iBioSim	Yes	No	Yes	No	Limited	No	No
CompuCell3D	Yes	No	No	No	Yes	No	Yes
COPASI	Yes	No	Yes	No	No	No	No
Cytosim	No	No	Yes	No	?	Yes	?
libroadrunner	Yes	No	Yes	No	No	No	No
massPy	Uses libroadrunner	Uses COBRApy	No	No	No	No
MCell	No	No	Yes	No	No	Yes	No
OpenCOR	Yes	No	No	No	No	No	No
PhysiBoSS
PhysiCell	Uses libroadrunner	No	No	No	Yes	?	Yes
PySCeS	Yes	No	?	No	No	No	No
pySB	Yes	No	No	No	No	No	No
ReaDDy
SBSCL	Yes	?	?	No	No	No	No
SBW	Yes	No	Yes	No	No	No	No
Smoldyn	No	No	Yes	No	No	Yes	No
Spatiocyte
SpringSaLaD
STEPS
Tellurium (software)	Uses libroadrunner
URDME
VCell	Yes	No	?	No	No	No	Single Cell

= Differential equation specific features =

class="wikitable" ! Name	Non-stiff solver	Stiff solver	Steady-state solver	Steady-state sensitivities	Time-dependent sensitivities	Bifurcation Analysis
iBioSim	Yes	Yes	No	No	?	No
CompuCell3D	Uses libroadrunner					NA
COPASI	Yes	Yes	Yes	Yes	?	Limited
libroadrunner	Yes	Yes	Yes	Yes	Yes	via AUTO2000 plugin
masspy	Uses libroadrunner
OpenCOR	Yes	Yes	?	?	?	No
PhysiBoSS
PhysiCell	Uses libroadrunner
PySCeS	Yes	Yes	Yes	Yes	?	Limited+
pySB	Yes	No	No	No	No	No
SBSCL
SBW	Uses C# edition of roadrunner					Yes
Tellurium (software)	Uses libroadrunner
VCell	Yes	Yes	No	No	No	No

= File format support and interface type =

class="wikitable" ! Name	Import	Export	Primary Interface	Network visualization (editing)
iBioSim	SBML	SBML	GUI	Yes (Yes)
CompuCell3D	Native XML specification format and SBML	Native XML	GUI/Python scripting	No
COPASI	Native XML specification format and SBML	Native XML and SBML	GUI	Yes (No)
libroadrunner	SBML	SBML	Python scripting	No
masspy	SBML	SBML	Python scripting	No

= Advanced features (where applicable) =

class="wikitable" ! Name	Stoichiometry matrix	Reduced stoich matrix	Conserved moiety analysis	Jacobian	MCA
COPASI	Yes	Yes	Yes	Yes	Yes
libroadrunner	Yes	Yes	Yes	Yes	Yes
masspy	via libroadrunner
PySCeS	Yes	Yes	Yes	Yes	Yes
VCell	?	?	?	?	Limited

= Other features =

class="wikitable" ! Name	Parameter Estimation	DAE support	Units support
iBioSim	No	?	?
ComputeCell3D	NA	NA	?
COPASI	Yes	Limited	Yes
libroadrunner	via Python packages	Limited	Yes
masspy	via Python packages	Limited	Yes

Particle-based simulators

Particle based simulators treat each molecule of interest as an individual particle in continuous space, simulating molecular diffusion, molecule-membrane interactions and chemical reactions.{{cite journal |last1=Schöneberg |first1=J |last2=Ullrich |first2=A |last3=Noé |first3=F |date=2014 |title=Simulation tools for particle-based reaction-diffusion dynamics in continuous space |journal=BMC Biophys |volume=7 |issue=1 |page=11 |doi=10.1186/s13628-014-0011-5 |pmid=25737778 |pmc=4347613 |doi-access=free }}

= Comparison of particle-based simulators =

The following list compares the features for several particle-based simulators. This table is edited from a version that was originally published in the Encyclopedia of Computational Neuroscience.{{cite book |last1=Andrews |first1=Steven S. |title=Encyclopedia of Computational Neuroscience |chapter=Particle-Based Stochastic Simulators |date=2018 |volume=10 |pages=978–1 |doi=10.1007/978-1-4614-7320-6_191-2|isbn=978-1-4614-7320-6 }} System boundaries codes: R = reflecting, A = absorbing, T = transmitting, P = periodic, and I = interacting. * Algorithm is exact but software produced incorrect results at the time of original table compilation. † These benchmark run times are not comparable with others due to differing levels of detail.

class="wikitable" ! Feature	MCell	Smoldyn	eGFRD	SpringSaLaD	ReaDDy
Time steps	~1 us	ns to ms	event-based	~10 ns	~0.1 ns to us
Molecules	points	points, spheres	spheres	multi-spheres	multi-spheres
Dimensions	2,3	1,2,3	3	3	3
System boundaries	R,A,P,T	R,A,P,T	P	R	P,I
Surfaces	triangle mesh	many primitives	-	1 flat surface	plane, sphere
Surface molecules	1/tile, 2 states	unlimited, 4 states	-	unlimited, 3 states	-
Excluded volume	-	excellent	exact	good	excellent
Multimers	states only	rule-based model	-	explicit	explicit
Allostery	-	yes	-	yes	-
Reaction accuracy	very good	excellent	exact*	excellent	excellent
Dissociation products	stochastic	fixed separation	adjacent	adjacent	adjacent
Molecule-surface interactions	good	excellent	-	to sites only	potentials
Long-range interactions	-	yes	-	-	yes
Benchmark run time	67 s	22 s	13 days†	9.1 months†	13 minutes
Distribution	executable	executable	self-compile	Java file	self-compile
User interface	GUI, text	text	text	GUI	Python script
Graphical output	excellent	good	partial support	partial support	good
Library interface	Python	C/C++, Python	-	-	Python
References	{{cite journal \|last1=Stiles \|first1=JR \|last2=Bartol \|first2=TM \|date=2001 \|title=Chapter 4, Monte Carlo methods for simulating realistic synaptic microphysiology using MCell \|series=In: Computational neuroscience, realistic modeling for experimentalists, De Schutter, E (ed.) \|publisher=CRC Press \|publication-place=Boca Raton \|pages=87–127}}{{cite journal \|last1=Stefan \|first1=MI \|last2=Bartol \|first2=TM \|last3=Sejnowski \|first3=TJ \|last4=Kennedy \|first4=MB \|date=2014 \|title=Multi-state modeling of biomolecules \|journal=PLOS Comput Biol \|volume=10 \|issue=9 \|pages=e1003844\|doi=10.1371/journal.pcbi.1003844 \|pmid=25254957 \|pmc=4201162 \|bibcode=2014PLSCB..10E3844S \|doi-access=free }}{{cite journal \|last1=Stiles \|first1=JR \|last2=Van Helden \|first2=D \|last3=Bartol \|first3=TM \|last4=Salpeter \|first4=EE \|last5=Salpeter \|first5=MM \|date=1996 \|title=Miniature endplate current rise times less than 100 microseconds from improved dual recordings can be modeled with passive acetylcholine diffusion from a synaptic vesicle \|journal=Proceedings of the National Academy of Sciences, USA \|volume=93 \|issue=12 \|pages=5747–5752\|doi=10.1073/pnas.93.12.5747 \|pmid=8650164 \|pmc=39132 \|bibcode=1996PNAS...93.5747S \|doi-access=free }}	{{cite journal \|last1=Andrews \|first1=SS \|date=2017 \|title=Smoldyn: particle-based simulation with rule-based modeling, improved molecular interaction and a library interface \|journal=Bioinformatics \|volume=33 \|issue=5 \|pages=710–717\|doi=10.1093/bioinformatics/btw700 \|pmid=28365760 \|doi-access=free }}{{cite journal \|last1=Andrews \|first1=SS \|last2=Addy \|first2=NJ \|last3=Brent \|first3=R \|last4=Arkin \|first4=AP \|date=2010 \|title=Detailed simulations of cell biology with Smoldyn 2.1 \|journal=PLOS Comput Biol \|volume=6 \|issue=3 \|pages=e1000705\|doi=10.1371/journal.pcbi.1000705 \|pmid=20300644 \|pmc=2837389 \|bibcode=2010PLSCB...6E0705A \|s2cid=2945597 \|doi-access=free }}	{{cite arXiv \|last1=Sokolowski \|first1=TR \|last2=ten Wolde \|first2=PR \|date=2017 \|title=Spatial-stochastic simulation of reaction-diffusion systems \|class=q-bio.MN \|eprint=1705.08669}}{{cite journal \|last1=Takahashi \|first1=K \|last2=Tănase-Nicola \|first2=S \|last3=Ten Wolde \|first3=PR \|date=2010 \|title=Spatio-temporal correlations can drastically change the response of a MAPK pathway \|journal=Proc Natl Acad Sci \|volume=107 \|issue=6 \|pages=2473–2478\|doi=10.1073/pnas.0906885107 \|pmid=20133748 \|pmc=2811204 \|arxiv=0907.0514 \|bibcode=2010PNAS..107.2473T \|doi-access=free }}{{cite journal \|last1=Tomita \|first1=M \|last2=Hashimoto \|first2=K \|last3=Takahashi \|first3=K \|last4=Shimizu \|first4=TS \|display-authors=et al. \|date=1999 \|title=E-cell: software environment for whole-cell simulation \|journal=Bioinformatics \|volume=15 \|issue=1 \|pages=72–84\|doi=10.1093/bioinformatics/15.1.72 \|pmid=10068694 \|doi-access=free }}	{{cite journal \|last1=Michalski \|first1=PJ \|last2=Loew \|first2=LM \|date=2016 \|title=SpringSaLaD: a spatial, particle-based biochemical simulation platform with excluded volume \|journal=Biophys J \|volume=110 \|issue=3 \|pages=523–529\|doi=10.1016/j.bpj.2015.12.026 \|pmid=26840718 \|pmc=4744174 \|bibcode=2016BpJ...110..523M }}	{{cite journal \|last1=Schöneberg \|first1=J \|last2=Noé \|first2=F \|date=2013 \|title=ReaDDy-a software for particle-based reaction-diffusion dynamics in crowded cellular environments \|journal=PLOS ONE \|volume=8 \|issue=9 \|pages=e74261\|doi=10.1371/journal.pone.0074261 \|pmid=24040218 \|pmc=3770580 \|bibcode=2013PLoSO...874261S \|doi-access=free }}

Model calibration software

Model calibration is a key activity when developing systems biology models. This table highlights some of the current model calibration tools available to systems biology modelers. The first table list tools that are SBML compatible.

class="wikitable"

!Tool

!PEtab Compatible

! P1

! P2

pyPESTO{{Cite arXiv|last1=Schälte

|first1=Yannik

|last2=Fröhlich |first2=Fabian

|last3=Jost |first3=Paul J.

|last4=Vanhoefer |first4=Jakob

|last5=Pathirana |first5=Dilan

|last6=Stapor |first6=Paul

|last7=Lakrisenko |first7=Polina

|last8=Wang |first8=Dantong

|last9=Raimúndez |first9=Elba

|last10=Merkt |first10=Simon

|last11=Schmiester

|first11=Leonard |last12=Städter

|first12=Philipp |last13=Grein |first13=Stephan

|last14=Dudkin |first14=Erika |last15=Doresic

|first15=Domagoj |date=2023

|title=pyPESTO: A modular and scalable tool for parameter estimation for dynamic models

|class=q-bio.QM

|eprint=2305.01821}}

|Yes

|NA

COPASI

| Yes

| NA

PEtab{{cite journal |last1=Schmiester |first1=Leonard |last2=Schälte |first2=Yannik |last3=Bergmann |first3=Frank T. |last4=Camba |first4=Tacio |last5=Dudkin |first5=Erika |last6=Egert |first6=Janine |last7=Fröhlich |first7=Fabian |last8=Fuhrmann |first8=Lara |last9=Hauber |first9=Adrian L. |last10=Kemmer |first10=Svenja |last11=Lakrisenko |first11=Polina |last12=Loos |first12=Carolin |last13=Merkt |first13=Simon |last14=Müller |first14=Wolfgang |last15=Pathirana |first15=Dilan |last16=Raimúndez |first16=Elba |last17=Refisch |first17=Lukas |last18=Rosenblatt |first18=Marcus |last19=Stapor |first19=Paul L. |last20=Städter |first20=Philipp |last21=Wang |first21=Dantong |last22=Wieland |first22=Franz-Georg |last23=Banga |first23=Julio R. |last24=Timmer |first24=Jens |last25=Villaverde |first25=Alejandro F. |last26=Sahle |first26=Sven |last27=Kreutz |first27=Clemens |last28=Hasenauer |first28=Jan |last29=Weindl |first29=Daniel |title=PEtab—Interoperable specification of parameter estimation problems in systems biology |journal=PLOS Computational Biology

|date=26 January 2021

|volume=17

|issue=1

|pages=e1008646

|doi=10.1371/journal.pcbi.1008646 |pmid=33497393 |pmc=7864467 |arxiv=2004.01154 |bibcode=2021PLSCB..17E8646S |doi-access=free }} is a community standard for specifying model calibration runs.

Legacy open-source software applications

The following list some very early software for modeling biochemical systems that were developed pre-1980s There are listed for historical interest.

class="wikitable" ! Name ! Description/Notability	Language	Terminus ante quemBased on earliest publication date
BIOSIM{{cite journal \|last1=Garfinkel \|first1=David \|title=A machine-independent language for the simulation of complex chemical and biochemical systems \|journal=Computers and Biomedical Research \|date=August 1968 \|volume=2 \|issue=1 \|pages=31–44 \|doi=10.1016/0010-4809(68)90006-2\|pmid=5743538 }}	The first ever recorded digital simulator of biochemical networks (by David Garfinkel)	FORTRAN IV	1968
KDF 9{{cite thesis \|last1=Burns \|first1=Jim \|title=Metabolic Control Anlaysis \|date=1 March 1973 \|doi=10.5281/zenodo.7240738}}	First simulator to support MCA. Developed by the late Jim Burns in Edinburgh	Early form of FORTRAN	1968
METASIM{{cite journal \|last1=Park \|first1=D.J.M. \|last2=Wright \|first2=B.E. \|title=Metasim, a general purpose metabolic simulator for studying cellular transformations \|journal=Computer Programs in Biomedicine \|date=March 1973 \|volume=3 \|issue=1 \|pages=10–26 \|doi=10.1016/0010-468X(73)90010-X\|pmid=4735157 }}	Early simulator by Park and Wright	PL/1	1973

The following list shows some of the software modeling applications that were developed in the 1980s and 1990s. There are listed for historical interest.

class="wikitable" ! Name ! Description/Notability	Language	SBML Support	Terminus ante quemBased on earliest publication date
[https://opencor.ws/cor COR]{{Cite journal \|last1=Garny \|first1=A. \|last2=Kohl \|first2=P. \|last3=Noble \|first3=D. \|date=2003-12-01 \|title=Cellular open resource (cor): a public cellml based environment for modeling biological function \|url=https://www.worldscientific.com/doi/abs/10.1142/S021812740300882X \|journal=International Journal of Bifurcation and Chaos \|volume=13 \|issue=12 \|pages=3579–3590 \|doi=10.1142/S021812740300882X \|bibcode=2003IJBC...13.3579G \|issn=0218-1274\|url-access=subscription }} \|First public CellML-based environment. \|Object Pascal \|Uses CellML \|2010
DBsolve{{cite journal \|last1=Goryanin \|first1=I. \|last2=Hodgman \|first2=T. C. \|last3=Selkov \|first3=E. \|title=Mathematical simulation and analysis of cellular metabolism and regulation \|journal=Bioinformatics \|date=1 September 1999 \|volume=15 \|issue=9 \|pages=749–758 \|doi=10.1093/bioinformatics/15.9.749\|pmid=10498775 \|doi-access=free }}	Early GUI based simulation platform.	C/C++	No	1999
E-Cell{{cite journal \|last1=Tomita \|first1=M \|last2=Hashimoto \|first2=K \|last3=Takahashi \|first3=K \|last4=Shimizu \|first4=T. \|last5=Matsuzaki \|first5=Y \|last6=Miyoshi \|first6=F \|last7=Saito \|first7=K \|last8=Tanida \|first8=S \|last9=Yugi \|first9=K \|last10=Venter \|first10=J. \|last11=Hutchison \|first11=C. \|title=E-CELL: software environment for whole-cell simulation \|journal=Bioinformatics \|date=1 January 1999 \|volume=15 \|issue=1 \|pages=72–84 \|doi=10.1093/bioinformatics/15.1.72\|pmid=10068694 \|doi-access=free }}	One of the earliest attempts at a whole-cell modeling platform.	C/C++	No	1999
Gepasi{{cite journal \|last1=Mendes \|first1=Pedro \|title=GEPASI: a software package for modelling the dynamics, steady states and control of biochemical and other systems \|journal=Bioinformatics \|date=1993 \|volume=9 \|issue=5 \|pages=563–571 \|doi=10.1093/bioinformatics/9.5.563\|pmid=8293329 }}	First GUI application that supported metabolic control analysis and parameter estimation.	C/C++	Yes	1993
Jarnac{{cite book \|last1=Sauro \|first1=Herbert \|title=JARNAC: a system for interactive metabolic analysis \|date=2000 \|publisher=Animating the Cellular Map: Proceedings of the 9th International Meeting on BioThermoKinetics \|pages=221–228}}	First GUI based application to support scripting in systems biology modeling.	Object Pascal	Yes	2000
JSim{{cite journal \|last1=Butterworth \|first1=Erik \|last2=Jardine \|first2=Bartholomew E. \|last3=Raymond \|first3=Gary M. \|last4=Neal \|first4=Maxwell L. \|last5=Bassingthwaighte \|first5=James B. \|title=JSim, an open-source modeling system for data analysis \|journal=F1000Research \|date=30 December 2013 \|volume=2 \|pages=288 \|doi=10.12688/f1000research.2-288.v1\|pmid=24555116 \|pmc=3901508 \|doi-access=free }}	First Java-based systems biology modeling platform	Java	Yes	2003
MetaMod{{cite journal \|last1=Hofmeyr \|first1=J. H. S. \|last2=Merwe \|first2=K. J. van der \|title=METAMOD: software for steady-state modelling and control analysis of metabolic pathways on the BBC microcomputer \|journal=Bioinformatics \|date=1986 \|volume=2 \|issue=4 \|pages=243–249 \|doi=10.1093/bioinformatics/2.4.243\|pmid=3450367 }}	One of the first PC-based systems biology simulators	BBC Micro	No	1986
MetaModel{{cite journal \|last1=Cornish-Bowden \|first1=Athel \|last2=Hofmeyr \|first2=Jan-Hendrik S. \|title=MetaModel: a program for modelling and control analysis of metabolic pathways on the IBM PC and compatibles \|journal=Bioinformatics \|date=1991 \|volume=7 \|issue=1 \|pages=89–93 \|doi=10.1093/bioinformatics/7.1.89\|pmid=2004280 }}	Early PC-based systems biology simulator	Turbo Pascal 5.0	No	1991
MIST{{cite journal \|last1=Ehlde \|first1=Magnus \|last2=Zacchi \|first2=Guido \|title=MIST: a user-friendly metabolic simulator \|journal=Bioinformatics \|date=1995 \|volume=11 \|issue=2 \|pages=201–207 \|doi=10.1093/bioinformatics/11.2.201\|pmid=7620994 }}	GUI based simulator	Borland Pascal 7.0	No	1995
SCAMP{{cite journal \|last1=Sauro \|first1=Herbert M. \|last2=Fell \|first2=David A. \|title=SCAMP: A metabolic simulator and control analysis program \|journal=Mathematical and Computer Modelling \|date=1991 \|volume=15 \|issue=12 \|pages=15–28 \|doi=10.1016/0895-7177(91)90038-9\|doi-access=free }}	First application to support metabolic control analysis and simulation on a PC	Pascal, later in C	No	1985 (Thesis)

References

Category:Systems biology

Bioinformatics

Category:Science software

Systems