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dc.contributor.authorGillman, MSen_US
dc.date.accessioned2017-09-26T08:05:07Z
dc.date.available2017-08-29en_US
dc.date.issued2017-09-20en_US
dc.date.submitted2017-08-29T14:15:09.137Z
dc.identifier.issn2049-9647en_US
dc.identifier.urihttp://qmro.qmul.ac.uk/xmlui/handle/123456789/25885
dc.description.abstractThis software implements a discrete time Markov chain model, used to model transitions between states when the transition probabilities are known a priori. It is highly configurable; the user supplies two text files, a "state transition table" and a "config file", to the Perl script genesis.pl. Given the content of these files, the script generates a set of C++ classes based on the State design pattern, and a main program, which can then be compiled and run. The C++ code generated is based on the specification in the text files. Both multiple branching and bi-directional transitions are allowed. The software has been used to model the natural histories of colorectal cancer in Mexico. Although written primarily to model such disease processes, it can be used in any process which depends on discrete states with known transition probabilities between those states. One suitable area may be in environmental modelling. A test suite is supplied with the distribution. Due to its high degree of configurability and flexibility, this software has good re-use potential. It is stored on the Figshare repository.en_US
dc.description.sponsorshipThis work was supported by Cancer Research UK C8162/A16892. This research utilised Queen Mary’s MidPlus computational facilities, supported by QMUL Research-IT and funded by EPSRC grant EP/K000128/1.en_US
dc.format.extent24 - ?en_US
dc.languageengen_US
dc.language.isoenen_US
dc.relation.ispartofJ Open Res Softwen_US
dc.rightsCC BY
dc.subjectC++en_US
dc.subjectMarkov chainen_US
dc.subjectMarkov processen_US
dc.subjectPerlen_US
dc.subjectdisease progressionen_US
dc.subjectmodellingen_US
dc.subjectprobabilitiesen_US
dc.subjectrandom number generationen_US
dc.subjectsimulationen_US
dc.subjectstate machineen_US
dc.subjectstate transitionsen_US
dc.titleGENESIS - The GENEric SImulation System for Modelling State Transitions.en_US
dc.typeArticle
dc.rights.holder(c) The Author(s) 2017.
dc.identifier.doi10.5334/jors.179en_US
pubs.author-urlhttps://www.ncbi.nlm.nih.gov/pubmed/28989704en_US
pubs.issue1en_US
pubs.notesNot knownen_US
pubs.organisational-group/Queen Mary University of London
pubs.organisational-group/Queen Mary University of London/Faculty of Medicine & Dentistry
pubs.organisational-group/Queen Mary University of London/Faculty of Medicine & Dentistry/Wolfson Institute of Preventive Medicine
pubs.organisational-group/Queen Mary University of London/Faculty of Medicine & Dentistry/Wolfson Institute of Preventive Medicine/Centre for Cancer Prevention
pubs.publication-statusPublisheden_US
pubs.volume5en_US
qmul.funderCancer screening & statistics::Cancer Research UKen_US


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