Formal Analysis of Uncertain Continuous Markov Chains in Systems Biology

Krishnendu Ghosh, Caroline Goodman

2024

Abstract

Data dependent abstraction for continuous-time Markov chain is often challenging given the incompleteness and imprecision of data. Uncertainty in the environment is modeled in the form of uncertain continuous-time Markov chain. In this work, a tractable model checking methodology, stochastic partial model set checking is formalized by approximation of the uncertain continuous-time Markov chain. The methodology was applied in querying to infer on a phylogenetic tree, constructed under uncertainty. Queries were posed on the formalism using continuous stochastic logic formula. Experimental results demonstrate the computational feasibility of the model.

Paper Citation

in Harvard Style

Ghosh K. and Goodman C. (2024). Formal Analysis of Uncertain Continuous Markov Chains in Systems Biology. In Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOINFORMATICS; ISBN 978-989-758-688-0, SciTePress, pages 519-526. DOI: 10.5220/0012466000003657

in Bibtex Style

@conference{bioinformatics24,
author={Krishnendu Ghosh and Caroline Goodman},
title={Formal Analysis of Uncertain Continuous Markov Chains in Systems Biology},
booktitle={Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOINFORMATICS},
year={2024},
pages={519-526},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012466000003657},
isbn={978-989-758-688-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOINFORMATICS
TI - Formal Analysis of Uncertain Continuous Markov Chains in Systems Biology
SN - 978-989-758-688-0
AU - Ghosh K.
AU - Goodman C.
PY - 2024
SP - 519
EP - 526
DO - 10.5220/0012466000003657
PB - SciTePress