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FUBAR: A Fast, Unconstrained Bayesian AppRoximation for Inferring Selection
Model-based analyses of natural selection often categorize sites into a relatively small number of site classes. Forcing each site to belong to one of these classes places unrealistic constraints on the distribution of selection parameters, which can result in misleading inference due to model missp...
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| Auteurs principaux: | , , , , , , |
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| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
Oxford University Press
2013
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3670733/ https://ncbi.nlm.nih.gov/pubmed/23420840 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/molbev/mst030 |
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