Сравнение методов

	Сетевой филогенетический анализ	Филогенетический анализ
Область	Биоинформатика	Биоинформатика
Семейство	Process / pipeline	Process / pipeline
Год появления	1992–2004 (foundational algorithms); broader development 1990s–2010s	1960s-1981 (distance trees ~1967; ML framework formalised 1981)
Автор метода	Hans-Jürgen Bandelt & Andreas Dress (split decomposition); David Bryant & Vincent Moulton (Neighbor-Net)	Joseph Felsenstein (maximum likelihood framework); Walter Fitch and Emanuel Margoliash (distance methods)
Тип	Computational phylogenetic method	Computational inference method
Основополагающий источник	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.	Felsenstein, J. (2004). Inferring Phylogenies. Sinauer Associates. ISBN: 978-0878931774
Другие названия	phylogenetic network, reticulate phylogenetics, split network analysis, evolutionary network inference	molecular phylogenetics, phylogenetic inference, evolutionary tree reconstruction, phylogenomics
Связанные	6	5
Сводка	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.	Phylogenetic analysis reconstructs the evolutionary history of organisms, genes, or proteins by comparing molecular sequence data and estimating the branching tree that best explains observed similarities and differences. Rooted in the work of Felsenstein and colleagues from the 1960s onward, it is a cornerstone technique in evolutionary biology, microbiology, epidemiology, and comparative genomics, supporting tasks from tracing viral outbreak origins to classifying novel species.