Blocking Gibbs sampling in very large probabilistic expert systems
International Journal of Human-Computer Studies - Special issue: real-world applications of uncertain reasoning
Introduction to Bayesian Networks
Introduction to Bayesian Networks
A simple method for finding a legal configuration in complex Bayesian networks
Statistics and Computing
Genetic restoration on complex pedigrees
Genetic restoration on complex pedigrees
Efficient rule-based haplotyping algorithms for pedigree data
RECOMB '03 Proceedings of the seventh annual international conference on Research in computational molecular biology
Graphical Models, Exponential Families, and Variational Inference
Foundations and Trends® in Machine Learning
Haplotype Inference in Complex Pedigrees
RECOMB 2'09 Proceedings of the 13th Annual International Conference on Research in Computational Molecular Biology
Addressing the concerns of the lacks family: quantification of kin genomic privacy
Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security
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The problem of multilocus linkage analysis is expressed as a graphical model, making explicit a previously implicit connection, and recent developments in the field are described in this context. A novel application of blocked Gibbs sampling for Bayesian networks is developed to generate inheritance matrices from an irreducible Markov chain. This is used as the basis for reconstruction of historical meiotic states and approximate calculation of the likelihood function for the location of an unmapped genetic trait. We believe this to be the only approach that currently makes fully informative multilocus linkage analysis possible on large extended pedigrees.