Beaumont, M. A. and Rannala, B. (2004) The Bayesian revolution in genetics. Nature Reviews Genetics, 5 (4). pp. 251-261. ISSN 1471-0056 doi: 10.1038/nrg1318
Abstract/Summary
Bayesian statistics allow scientists to easily incorporate prior knowledge into their data analysis. Nonetheless, the sheer amount of computational power that is required for Bayesian statistical analyses has previously limited their use in genetics. These computational constraints have now largely been overcome and the underlying advantages of Bayesian approaches are putting them at the forefront of genetic data analysis in an increasing number of areas.
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| Item Type | Article |
| URI | https://reading-clone.eprints-hosting.org/id/eprint/10429 |
| Identification Number/DOI | 10.1038/nrg1318 |
| Refereed | Yes |
| Divisions | Life Sciences > School of Biological Sciences |
| Uncontrolled Keywords | SINGLE-NUCLEOTIDE POLYMORPHISMS, MAXIMUM-LIKELIHOOD-ESTIMATION, LOCAL, SEQUENCE ALIGNMENT, CHAIN MONTE-CARLO, LINKAGE-DISEQUILIBRIUM, POPULATION-GROWTH, DNA-SEQUENCES, MARKOV-CHAIN, HUMAN GENOME, MICROSATELLITE ANALYSIS |
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