Literature DB >> 23792213

CytoBayesJ: software tools for Bayesian analysis of cytogenetic radiation dosimetry data.

Elizabeth A Ainsbury1, Volodymyr Vinnikov, Pedro Puig, Nataliya Maznyk, Kai Rothkamm, David C Lloyd.   

Abstract

A number of authors have suggested that a Bayesian approach may be most appropriate for analysis of cytogenetic radiation dosimetry data. In the Bayesian framework, probability of an event is described in terms of previous expectations and uncertainty. Previously existing, or prior, information is used in combination with experimental results to infer probabilities or the likelihood that a hypothesis is true. It has been shown that the Bayesian approach increases both the accuracy and quality assurance of radiation dose estimates. New software entitled CytoBayesJ has been developed with the aim of bringing Bayesian analysis to cytogenetic biodosimetry laboratory practice. CytoBayesJ takes a number of Bayesian or 'Bayesian like' methods that have been proposed in the literature and presents them to the user in the form of simple user-friendly tools, including testing for the most appropriate model for distribution of chromosome aberrations and calculations of posterior probability distributions. The individual tools are described in detail and relevant examples of the use of the methods and the corresponding CytoBayesJ software tools are given. In this way, the suitability of the Bayesian approach to biological radiation dosimetry is highlighted and its wider application encouraged by providing a user-friendly software interface and manual in English and Russian.
Copyright © 2013 Elsevier B.V. All rights reserved.

Keywords:  Bayesian; Biological dosimetry (biodosimetry); Hermite; Negative binomial; Neyman type-A; Radiation cytogenetics

Mesh:

Year:  2013        PMID: 23792213     DOI: 10.1016/j.mrgentox.2013.06.005

Source DB:  PubMed          Journal:  Mutat Res        ISSN: 0027-5107            Impact factor:   2.433


  7 in total

1.  A Bayesian hierarchical method to account for random effects in cytogenetic dosimetry based on calibration curves.

Authors:  Shuhei Mano; Yumiko Suto
Journal:  Radiat Environ Biophys       Date:  2014-08-26       Impact factor: 1.925

2.  A new Bayesian model applied to cytogenetic partial body irradiation estimation.

Authors:  Manuel Higueras; Pedro Puig; Elizabeth A Ainsbury; Volodymyr A Vinnikov; Kai Rothkamm
Journal:  Radiat Prot Dosimetry       Date:  2015-06-11       Impact factor: 0.972

Review 3.  State-of-the-Art Advances in Radiation Biodosimetry for Mass Casualty Events Involving Radiation Exposure.

Authors:  Mary Sproull; Kevin Camphausen
Journal:  Radiat Res       Date:  2016-10-06       Impact factor: 2.841

4.  Application of Bayesian statistics for radiation dose assessment in mixed beta-gamma fields.

Authors:  I Słonecka; J Krasowska; Z Baranowska; K W Fornalski
Journal:  Radiat Environ Biophys       Date:  2021-04-16       Impact factor: 1.925

5.  A new inverse regression model applied to radiation biodosimetry.

Authors:  Manuel Higueras; Pedro Puig; Elizabeth A Ainsbury; Kai Rothkamm
Journal:  Proc Math Phys Eng Sci       Date:  2015-02-08       Impact factor: 2.704

6.  Simplified Bayesian method: application in cytogenetic biological dosimetry of mixed n + γ radiation fields.

Authors:  I Słonecka; K Łukasik; K W Fornalski
Journal:  Radiat Environ Biophys       Date:  2018-11-21       Impact factor: 1.925

7.  Analytical and quasi-Bayesian methods as development of the iterative approach for mixed radiation biodosimetry.

Authors:  Iwona Słonecka; Krzysztof Łukasik; Krzysztof W Fornalski
Journal:  Radiat Environ Biophys       Date:  2018-06-04       Impact factor: 1.925

  7 in total

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