Bayesian hidden Markov models in DNA sequence segmentation using R: the case of Simian Vacuolating virus (SV40)

Bayesian hidden Markov models in DNA sequence segmentation using R: the case of Simian Vacuolating virus (SV40)

Segmentation models aim to partition compositionally heterogeneous domains into homogeneous segments which may be reflective of biological function. Due to the latent nature of the segments a natural approach to segmentation that has gained favour recently uses Bayesian hidden Markov models (HMMs)....

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Bibliographic Details
Main Authors: Totterdell, J.A., Nur, Darfiana, Mengersen, K.L.
Format: Journal Article
Language:English
Published: TAYLOR & FRANCIS LTD 2017
Subjects:
Science & Technology
Technology
Physical Sciences
Computer Science, Interdisciplinary Applications
Statistics & Probability
Computer Science
Mathematics
Bayesian modelling
DNA sequence
data augmentation
Gibbs sampler algorithm
hidden Markov models
label switching algorithm
R statistical software
segmentation modelling
Simian Vacuolating virus (SV40)
PROBABILISTIC FUNCTIONS
STATISTICAL-ANALYSIS
GENOME
CHAINS
Online Access:http://hdl.handle.net/20.500.11937/79609

Internet

http://hdl.handle.net/20.500.11937/79609

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