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Bayesian inference in multipoint gene mapping
Author(s) -
STEPHENS D. A.,
SMITH A. F. M.
Publication year - 1993
Publication title -
annals of human genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.537
H-Index - 77
eISSN - 1469-1809
pISSN - 0003-4800
DOI - 10.1111/j.1469-1809.1993.tb00887.x
Subject(s) - inference , markov chain monte carlo , permutation (music) , bayesian probability , bayesian inference , markov chain , computational biology , computer science , algorithm , basis (linear algebra) , mathematics , artificial intelligence , machine learning , biology , physics , geometry , acoustics
Summary The problem of rodering and mapping genes on the basis of recombinant data and radiation hybrid data is formulated as a problem of Bayesian inference for an unknown permutation. The challenging computational problems posed by this approach are shown to be resolvable using Markov chain Monte Carlo methods.