A novel parallel approach to the likelihood-based estimation of admixture in population geneticsGiovannini, A., Zanghirati, G., Beaumont, M. A., Chikhi, L. and Barbujani, G. (2009) A novel parallel approach to the likelihood-based estimation of admixture in population genetics. Bioinformatics, 25 (11). pp. 1440-1441. ISSN 1367-4803 Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1093/bioinformatics/btp136 Abstract/SummaryInferring population admixture from genetic data and quantifying it is a difficult but crucial task in evolutionary and conservation biology. Unfortunately state-of-the-art probabilistic approaches are computationally demanding. Effectively exploiting the computational power of modern multiprocessor systems can thus have a positive impact to Monte Carlo-based simulation of admixture modeling. A novel parallel approach is briefly described and promising results on its message passing interface (MPI)-based C implementation are reported.
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