Salīdzināt metodes

	Filoģenētiskā laika sēriju analīze	Beiesa filogenētiskā analīze
Nozare	Bioinformātika	Bioinformātika
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	2000s (molecular clock methods earlier; BEAST framework 2007)	1996–2001
Autors	Alexei J. Drummond, Andrew Rambaut, and colleagues	Rannala & Yang (1996); operationalized by Huelsenbeck et al. (MrBayes, 2001)
Tips	Evolutionary bioinformatics pipeline	Probabilistic inference method
Pirmavots	Drummond, A. J., & Rambaut, A. (2007). BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evolutionary Biology, 7, 214.	Ronquist, F., & Huelsenbeck, J. P. (2003). MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics, 19(12), 1572–1574.
Citi nosaukumi	temporal phylogenetics, time-resolved phylogenetics, molecular clock phylogenetics, phylodynamics	Bayesian phylogenetics, Bayesian inference of phylogeny, MCMC phylogenetics, Bayesian molecular phylogenetics
Saistītās	6	3
Kopsavilkums	Time-series phylogenetic analysis reconstructs the evolutionary history of organisms or genetic variants using sequences sampled at known time points. By incorporating sampling dates directly into the model, it estimates divergence times, substitution rates, and ancestral relationships on an absolute timescale — making it essential for studying viral outbreaks, ancient DNA dynamics, and rapid microbial evolution.	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.