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| Phân tích phát sinh loài dựa trên mạng lưới× | Phân tích phát sinh loài Bayes× | |
|---|---|---|
| Lĩnh vực | Tin sinh học | Tin sinh học |
| Họ | Process / pipeline | Process / pipeline |
| Năm ra đời≠ | 1992–2004 (foundational algorithms); broader development 1990s–2010s | 1996–2001 |
| Người khởi xướng≠ | Hans-Jürgen Bandelt & Andreas Dress (split decomposition); David Bryant & Vincent Moulton (Neighbor-Net) | Rannala & Yang (1996); operationalized by Huelsenbeck et al. (MrBayes, 2001) |
| Loại≠ | Computational phylogenetic method | Probabilistic inference method |
| Công trình gốc≠ | Bandelt, H.-J., & Dress, A. W. M. (1992). Split decomposition: A new and useful approach to phylogenetic analysis of distance data. Molecular Phylogenetics and Evolution, 1(3), 242–252. link ↗ | Ronquist, F., & Huelsenbeck, J. P. (2003). MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics, 19(12), 1572–1574. DOI ↗ |
| Tên gọi khác | phylogenetic network, reticulate phylogenetics, split network analysis, evolutionary network inference | Bayesian phylogenetics, Bayesian inference of phylogeny, MCMC phylogenetics, Bayesian molecular phylogenetics |
| Liên quan≠ | 6 | 3 |
| Tóm tắt≠ | Network-based phylogenetic analysis constructs graph-structured representations of evolutionary relationships that explicitly accommodate reticulate events — including hybridization, horizontal gene transfer, recombination, and incomplete lineage sorting — which strictly bifurcating phylogenetic trees cannot represent. Instead of forcing sequences into a single bifurcating tree, the method infers splits or reticulations in the data and visualises them as a network, revealing conflicting phylogenetic signals that are biologically informative. | 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. |
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