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  4. The Metropolized Partial Importance Sampling MCMC mixes slowly on minimal reversal rearrangement paths
 
research article

The Metropolized Partial Importance Sampling MCMC mixes slowly on minimal reversal rearrangement paths

Miklos, I.
•
Melykuti, B.
•
Swenson, K. M.  
2010
IEEE/ACM Trans. on Computational Biology and Bioinformatics

Markov chain Monte Carlo has been the standard technique for inferring the posterior distribution of genome rearrangement scenarios under a Bayesian approach. We present here a negative result on the rate of convergence of the generally used Markov chains. We prove that the relaxation time of the Markov chains walking on the optimal reversal sorting scenarios might grow exponentially with the size of the signed permutations, namely, with the number of syntheny blocks.

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Type
research article
DOI
10.1109/TCBB.2009.26
Web of Science ID

WOS:000283559100019

Author(s)
Miklos, I.
Melykuti, B.
Swenson, K. M.  
Date Issued

2010

Published in
IEEE/ACM Trans. on Computational Biology and Bioinformatics
Volume

7

Issue

4

Start page

763

End page

767

Subjects

Stochastic programming

•

Markov processes

•

analysis of algorithms and problem complexity

•

biology and genetics

•

Mitochondrial Genome Arrangements

•

Bayesian Phylogenetic Inference

•

Markov-Chains

•

Signed Permutations

•

Transpositions

•

Algorithm

•

Sequence

•

Distance

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LCBB  
Available on Infoscience
May 1, 2009
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/38209
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