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Finding protein thermostability and spin-coupling constant using Bayesian statistics

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An Erratum to this article was published on 04 December 2014

Abstract

This paper outlines the use of Bayesian statistics to find the thermostability and spin-coupling constant of protein. Thermostability is an important factor in protein efficacy; modeling it lets us find the mutation temperature of a protein. This is important since the temperature affects protein function. The spin-coupling constant provides high-level structure information about bond angles and rotation in a protein. We have used Bayesian statistics (MCMC) to find the unknown parameters for these two models. Predictive models using the parameters found with this method show good results.

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Acknowledgments

The authors would like to thank Professor Linxiang Zhou for his help with this work.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Oakland University, Rochester, MI, 48309-4401, USA

    Wenjin Zhou & Allison M. Rossetto

Authors
  1. Wenjin Zhou
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  2. Allison M. Rossetto
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Correspondence to Wenjin Zhou.

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Zhou, W., Rossetto, A.M. Finding protein thermostability and spin-coupling constant using Bayesian statistics. J Math Chem 53, 151–161 (2015). https://doi.org/10.1007/s10910-014-0416-z

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  • DOI: https://doi.org/10.1007/s10910-014-0416-z

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