方法证据记录
Bayesian Phylogenetic Analysis
Bayesian phylogenetic analysis uses Bayes' theorem and Markov chain Monte Carlo (MCMC) sampling to estimate the posterior probability distribution over phylogenetic trees and model parameters given observed sequence data. Unlike bootstrapped maximum-likelihood methods that return a single best tree, Bayesian inference yields a credible set of trees with associated posterior probabilities, providing a principled measure of phylogenetic uncertainty. It is the dominant framework for estimating divergence times and ancestral relationships in molecular evolution.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Bayesian Phylogenetic Analysis using Markov Chain Monte Carlo
分类方法记录 · process-pipeline / bioinformatics
- Ronquist, F., & Huelsenbeck, J. P. (2003). MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics, 19(12), 1572–1574. · DOI 10.1093/bioinformatics/btg180
- Drummond, A. J., & Rambaut, A. (2007). BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evolutionary Biology, 7(1), 214. · DOI 10.1186/1471-2148-7-214
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