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Analyzing Single-Molecule Protein Transportation Experiments via Hierarchical Hidden Markov Models

Chen, Yang and Shen, Kuang and Shan, Shu-ou and Kou, S. C. (2016) Analyzing Single-Molecule Protein Transportation Experiments via Hierarchical Hidden Markov Models. Journal of the American Statistical Association, 111 (515). pp. 951-966. ISSN 0162-1459. PMCID PMC5606165. http://resolver.caltech.edu/CaltechAUTHORS:20161117-073554872

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Abstract

To maintain proper cellular functions, over 50% of proteins encoded in the genome need to be transported to cellular membranes. The molecular mechanism behind such a process, often referred to as protein targeting, is not well understood. Single-molecule experiments are designed to unveil the detailed mechanisms and reveal the functions of different molecular machineries involved in the process. The experimental data consist of hundreds of stochastic time traces from the fluorescence recordings of the experimental system. We introduce a Bayesian hierarchical model on top of hidden Markov models (HMMs) to analyze these data and use the statistical results to answer the biological questions. In addition to resolving the biological puzzles and delineating the regulating roles of different molecular complexes, our statistical results enable us to propose a more detailed mechanism for the late stages of the protein targeting process.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1080/01621459.2016.1140050 DOIArticle
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5606165PubMed CentralArticle
ORCID:
AuthorORCID
Shan, Shu-ou0000-0002-6526-1733
Additional Information:© 2016 American Statistical Association. Received 01 Aug 2014, Accepted author version posted online: 02 Feb 2016, Published online: 18 Oct 2016. S. Shan’s research is supported in part by NIH grant GM078024 and the Gordon and Betty Moore Foundation through Grant GBMF2939. S. C. Kou’s research is supported in part by grants from NSF and ARO.
Funders:
Funding AgencyGrant Number
NIHGM078024
Gordon and Betty Moore FoundationGBMF2939
NSFUNSPECIFIED
Army Research Office (ARO)UNSPECIFIED
Subject Keywords:Conformational change, FRET, Hierarchical model, MCMC (Markov chain Monte Carlo), Model checking, Protein targeting
Issue or Number:515
PubMed Central ID:PMC5606165
Record Number:CaltechAUTHORS:20161117-073554872
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20161117-073554872
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:72088
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:17 Nov 2016 20:04
Last Modified:12 Aug 2019 21:41

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