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STATIONARITY AND INFERENCE IN MULTISTATE PROMOTER MODELS OF STOCHASTIC GENE EXPRESSION VIA STICK-BREAKING MEASURES.
- Source :
-
SIAM Journal on Applied Mathematics . 2022, Vol. 82 Issue 6, p1953-1986. 34p. - Publication Year :
- 2022
-
Abstract
- In a general stochastic multistate promoter model of dynamic messenger ribonucleic acid (mRNA)/protein interactions, we identify the stationary joint distribution of the promoter state, mRNA, and protein levels through an explicit "stick-breaking" construction perhaps of interest in itself. This derivation is a constructive advance over previous work where the stationary distribution is solved only in restricted cases. Moreover, the stick-breaking construction allows us to sample directly from the stationary distribution, permitting inference procedures and model selection. In this context, we discuss numerical Bayesian experiments to illustrate the results. [ABSTRACT FROM AUTHOR]
- Subjects :
- *MESSENGER RNA
*STOCHASTIC models
*GENE expression
Subjects
Details
- Language :
- English
- ISSN :
- 00361399
- Volume :
- 82
- Issue :
- 6
- Database :
- Academic Search Index
- Journal :
- SIAM Journal on Applied Mathematics
- Publication Type :
- Academic Journal
- Accession number :
- 161705883
- Full Text :
- https://doi.org/10.1137/21M1440876