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News | Downloading GNU MCSim | Documentation | Citation | Installation | Mailing lists | Contributed material and related links |Getting involved |Licensing
GNU MCSim
GNU MCSim is a simulation package, written inC, which allows you to:
- design and run your own statistical or simulation models (using algebraic or differential equations),
- perform Monte Carlo stochastic simulations,
- do Bayesian inference through Markov Chain Monte Carlo simulations,
- formally optimize experimental designs.
News
June 3rd, 2020 - Release of GNU MCSim version 6.2.0.
Version 6.2.0 offers various extensions, but most notablyparallelization of Monte Carlo, SetPoints and MCMC simulations, if youhave a multi-processor machine and MPI installed.
Downloading GNU MCSim
The latest version of GNU MCSim (and older versions) can befound on anyGNU mirror.
You can also download it from the main GNU ftp server:
- via HTTP athttp://ftp.gnu.org/gnu/mcsim/
- via FTP atftp://ftp.gnu.org/gnu/mcsim/.
The gzipped tar archive contains:
- A User's Manual (in Texinfo, pdf and HTML formats)
- The ASCII source code of the Mod program (to preprocess your models)
- The ASCII source code of the GNU MCSim routines (to link with your models)
- Examples of model and simulation files
GNU MCSim development is hosted on savannah.gnu.org. Seethe MCSim projectpage on Savannah, where the latest development sources arepublicly available.
Verifying GNU MCSim Signature
To verify the signature of the GNU MCSim tarball, please download boththe mcsim-X.Y.Z.tar.gz and mcsim-X.Y.Z.tar.gz.sig files. The key usedto sign the official releases can be foundhere.
The signature can be verified with the following steps:
Documentation
The User's manual for GNU MCSimis available online, asis documentation for most GNU software. You mayalso find more information about GNU MCSim by runninginfo mcsim,or by looking at/usr/share/mcsim/doc,or similar directories on your system.
Your can download a PDF version of the manual by clicking here.
Dr. Nan-Hung Hsieh (at Texas A&M) contributed a series of nice tutorial slides (PDF here) for GNU MCSim.
Citation
To cite GNU MCSim in publications you should refer to this page or to:Bois F., 2009, GNU MCSim: Bayesian statistical inference for SBML-coded systems biology models Bioinformatics, 25:1453-1454, doi: 10.1093/bioinformatics/btp162.
Installation
To install GNU MCSim, you will need a C compiler and linker to compilethe sources and obtain executables.For any machine we recommend theGNU gcc compiler, but standard C compilers should also work.
Versions 5.0.0 up to 5.3.1 required GNU Scientific Library(gsl, and its companion gslcblas) to be installed. With version 5.4.0,GNU gsl becomes optional (but recommended).
Versions above 5.4.0 also prefers libSBML v4.2.0 or above to beinstalled, but that is not needed if you do not want to read SBML model files.
Version 6.0.0 and later releases can make use of the Sundial'sCVODES integrator, if you install the CVODES library. You should useversion 2.7.0 of that library. Later versions have restructured theirfiles and will probably not work. We provide CVODES version 2.7.0 here. It is also distributed by Ubuntu(as of March 11, 2020), or you can fetch it from the archives of theSundials web site.
Version 6.2.0 and later releases can take advantage ofmulti-processors machines to run parallel simulations. You need toinstall a MPI library (for example from the Open MPI project).
The user's manual (online here)provides detailed instructions for installation for severalplatforms.
The basic tools needed to build and run GNU MCSim are not available tomost users of Windows systems. At least two simple options exists for them:
- The R software (http://www.r-project.org/), installed together with Rtools (this requires administrator's rights), can compile and run GNU MCSim models.
- Pr. W. Chiu, of Texas A&M, proposes an alternative using minGW. It requires no administrator's rights. However, only 32 bits code is generated (it is at bit slower).
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Mailing lists
GNU MCSimhas the following mailing lists:
- bug-mcsim is used to discuss most aspects of GNU MCSim, including development and enhancement requests, as well as bug reports.
- help-mcsim is for general user help and discussion.
Announcements about GNU MCSimand most other GNU software are made oninfo-gnu(archive). See also info-mcsim.
Security reports that should not be made immediately public can besent directly to the maintainer. If there is no response to an urgentissue, you can escalate to the generalsecuritymailing list for advice.
You can also look at the same lists, GNU MCSim help, andGNU MCSim bug report, on the gmane portal which has spam control.
Contributed material and related links
- Supplementary material for the article 'GNU MCSim: Bayesian statistical inference for SBML-coded systems biology models', Bioinformatics, 1 June 2009; 25: 1453 - 1454. That paper demonstrates the application of GNU MCSim MCMC sampling, optimal design and multilevel modeling to SBML models.
- Supplementary material containing all model and input files for predicting interactions between benzene, toluene, ethylbenzene and xylene via PBPK and systems biology coupling. See the article 'A mechanistic modeling framework for predicting metabolic interactions in complex mixtures', Environmental Health Perspectives, 2011; 119:1712-1718.
- Supplementary material containing all model and input files for simulated tempering demonstrations (2019).
- Report describing the OpenCAT model (PBPK model with multi-compartment gut) (2020).
- A PDF software validation report for version 5.0.0 can be found here. (The bug with the half-normal distribution it mentions has been fixed in version 5.1.0 and later versions.)
- A nice quick reference card, again by Bill.
Getting involved
Development of GNU MCSim,and GNU in general, is a volunteer effort, and you can contribute. Forinformation, please read How to help GNU. If you'dlike to get involved, it's a good idea to join the discussion mailinglist (see above).
- Development
- For development sources, issue trackers, and otherinformation, please see theGNU MCSimproject pageat savannah.gnu.org.
- Maintainer
- GNU MCSimis currently being maintained by Frederic Y. Bois.Please use the mailing lists for contact.
Licensing
GNU MCSimis free software; you can redistribute it and/or modify it under theterms of the GNU General Public License as published by the FreeSoftware Foundation; either version 3 of the License, or (at youroption) any later version.
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BlockTreat is a general frequentist Monte Carlo program for block and treatment tests, tests with matching, k-sample tests, and tests for independence. BlockTreat is written in Java.
excelmontecarlo.com – (Linux only) a full tutorial on Monte Carlo simulation in Excel without using add-ins. Good introduction to core concepts and some advanced techniques.
Gnumeric is a fast, free open source spreadsheet program with considerably more power than most of the competition (including Excel). Monte Carlo functions are built into the spreadsheet along with other advanced statistical functions.
MCS uses Monte Carlo techniques in combination with PERT (Program Evaluation and Review Technique) to estimate project timescales. This is an open source product and developed in Java.
MonteCarlito is a free Excel add-in with support for both Windows and OS X versions of Excel. It supports some standard statistical functions (mean, median, standard error, variance, skewness, kurtosis), high-speed simulation and because it is open source, is extendible.
SIMTOOLS adds statistical functions and procedures for doing Monte Carlo simulation and risk analysis in spreadsheets, and adds to Excel 32 statistical functions, listed in six categories:
- Inverse cumulative-probability functions.
- Functions for working with correlations among random variables
- Functions for decision analysis
- Functions for analyzing discrete probability distributions
- Functions for regression analysis
- Functions for randomly generating discrete distributions
SIMTOOLS.XLA also adds three macro procedures to the Excel Tools menu: SIMULATION TABLE, ITERATIVE PROCESS, COMBINE ROWS
SimulAr is a program developed as a complement of Microsoft Excel (Add-in) and it is characterized by its simplicity and flexibility
Tukhi is a free Excel add-in with the following features:
- High performance Monte Carlo simulations.
- Data driven simulations using SQL Queries.
- Simulations can be nested inside of simulations.
- Use any random number generators.
- No limit on the number of iterations.
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XLSim – This is a free add-in for Excel and is used by many large corporations. It supports distribution strings (DIST technology) a widely acclaimed method for communicating risk and uncertainty. Tutorials and examples are included with the download in addition to very good documentation.
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YASAI was developed for teaching elementary Monte Carlo simulation in Microsoft Excel. It was to be simple to use for mathematically unsophisticated beginning students, and could be used and installed easily without system administrator privilege. YASAI may run simulations slower than commercial products, since all the random number generation code is interpreted in Visual Basic.
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YASAIw – A Monte Carlo simulation add-in for Microsoft Excel. This add-in is a free open-source framework for Monte Carlo simulation in Excel. YASAIw is a modification of the original YASAI add-in that was developed by Rutgers University. The modified version (YASAIw) adds several new features including more distributions, correlated random variables, sensitivity analysis, and the ability to run user-defined macros during simulation.