Confronta i metodi

	Analisi Filogenetica di Serie Temporali	Analisi filogenetica Bayesiana
Campo	Bioinformatica	Bioinformatica
Famiglia	Process / pipeline	Process / pipeline
Anno di origine	2000s (molecular clock methods earlier; BEAST framework 2007)	1996–2001
Ideatore	Alexei J. Drummond, Andrew Rambaut, and colleagues	Rannala & Yang (1996); operationalized by Huelsenbeck et al. (MrBayes, 2001)
Tipo	Evolutionary bioinformatics pipeline	Probabilistic inference method
Fonte seminale	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.
Alias	temporal phylogenetics, time-resolved phylogenetics, molecular clock phylogenetics, phylodynamics	Bayesian phylogenetics, Bayesian inference of phylogeny, MCMC phylogenetics, Bayesian molecular phylogenetics
Correlati	6	3
Sintesi	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.