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Paper   IPM / Biological Sciences / 15740
School of Biological Sciences
  Title:   Bayesian comparison of protein structures using partial Procrustes distance
1.  Nassim Ejlali
2.  Mohammad Reza Faghihi
3.  Mehdi Sadeghi
  Status:   Published
  Journal: Statistical applications in genetics and molecular biology
  No.:  4
  Vol.:  16
  Year:  2017
  Pages:   243-257 (https://doi.org/10.1515/sagmb-2016-0014)
  Supported by:  IPM
An important topic in bioinformatics is the protein structure alignment. Some statistical methods have been proposed for this problem, but most of them align two protein structures based on the global geometric information without considering the effect of neighbourhood in the structures. In this paper, we provide a Bayesian model to align protein structures, by considering the effect of both local and global geometric information of protein structures. Local geometric information is incorporated to the model through the partial Procrustes distance of small substructures. These substructures are composed of β-carbon atoms from the side chains. Parameters are estimated using a Markov chain Monte Carlo (MCMC) approach. We evaluate the performance of our model through some simulation studies. Furthermore, we apply our model to a real dataset and assess the accuracy and convergence rate. Results show that our model is much more efficient than previous approaches.
Published Online: 2017-09-01

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