Clumped-MCEM: Inference for multistep transcriptional processes.
Mass action kinetics
Model reduction
Multistep promoter model
Parameter inference
Time-series data
Journal
Computational biology and chemistry
ISSN: 1476-928X
Titre abrégé: Comput Biol Chem
Pays: England
ID NLM: 101157394
Informations de publication
Date de publication:
Aug 2019
Aug 2019
Historique:
received:
16
11
2018
revised:
20
06
2019
accepted:
10
07
2019
pubmed:
20
8
2019
medline:
24
10
2019
entrez:
19
8
2019
Statut:
ppublish
Résumé
Many biochemical events involve multistep reactions. Among them, an important biological process that involves multistep reaction is the transcriptional process. A widely used approach for simplifying multistep reactions is the delayed reaction method. In this work, we devise a model reduction strategy that represents several OFF states by a single state, accompanied by specifying a time delay for burst frequency. Using this model reduction, we develop Clumped-MCEM which enables simulation and parameter inference. We apply this method to time-series data of endogenous mouse glutaminase promoter, to validate the model assumptions and infer the kinetic parameters. Further, we compare efficiency of Clumped-MCEM with state-of-the-art methods - Bursty MCEM
Identifiants
pubmed: 31422018
pii: S1476-9271(18)30855-7
doi: 10.1016/j.compbiolchem.2019.107092
pii:
doi:
Substances chimiques
Glutaminase
EC 3.5.1.2
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
16-20Informations de copyright
Copyright © 2019 Elsevier Ltd. All rights reserved.