Unknown

Dataset Information

0

GENESIS - The GENEric SImulation System for Modelling State Transitions.


ABSTRACT: This 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.

SUBMITTER: Gillman MS 

PROVIDER: S-EPMC5627703 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

altmetric image

Publications

GENESIS - The GENEric SImulation System for Modelling State Transitions.

Gillman Matthew S MS  

Journal of open research software 20170901 1


This software implements a discrete time Markov chain model, used to model transitions between states when the transition probabilities are known <i>a priori</i>. 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 base  ...[more]

Similar Datasets

| S-EPMC7405596 | biostudies-literature
| S-EPMC3199247 | biostudies-literature
| S-EPMC5906913 | biostudies-literature
| S-EPMC9644236 | biostudies-literature
| S-EPMC7343527 | biostudies-literature
| S-EPMC8789151 | biostudies-literature
| S-EPMC5489344 | biostudies-literature
| S-EPMC5774699 | biostudies-literature
| S-EPMC3488205 | biostudies-literature
| S-EPMC10539353 | biostudies-literature