scholarly journals Combinatorial Scoring of Phylogenetic Networks

2016 ◽  
pp. 560-572 ◽  
Author(s):  
Nikita Alexeev ◽  
Max A. Alekseyev
Keyword(s):  
Phylogenetic Networks

scholarly journals Biochemical and phylogenetic networks-II: X-trees and phylogenetic trees

2021 ◽  
Vol 59 (3) ◽  
pp. 699-718
Author(s):  
R. Sundara Rajan ◽  
A. Arul Shantrinal ◽  
K. Jagadeesh Kumar ◽  
T. M. Rajalaxmi ◽  
Indra Rajasingh ◽  
...  
Keyword(s):  
Phylogenetic Trees ◽  
Phylogenetic Networks

scholarly journals Inferring Phylogenetic Networks Using PhyloNet

2018 ◽  
Vol 67 (4) ◽  
pp. 735-740 ◽  
Author(s):  
Dingqiao Wen ◽  
Yun Yu ◽  
Jiafan Zhu ◽  
Luay Nakhleh
Keyword(s):  
Phylogenetic Networks

scholarly journals Ranking top-k trees in tree-based phylogenetic networks

2019 ◽  
Author(s):  
Momoko Hayamizu ◽  
Kazuhisa Makino
Keyword(s):  
Optimal Algorithm ◽  
Linear Time ◽  
Fundamental Problem ◽  
Phylogenetic Network ◽  
Reticulate Evolution ◽  
Interesting Property ◽  
Biological Data ◽  
Phylogenetic Networks ◽  
Linear Delay ◽  
Algorithmic Problems

Abstract 'Tree-based' phylogenetic networks provide a mathematically-tractable model for representing reticulate evolution in biology. Such networks consist of an underlying 'support tree' together with arcs between the edges of this tree. However, a tree-based network can have several such support trees, and this leads to a variety of algorithmic problems that are relevant to the analysis of biological data. Recently, Hayamizu (arXiv:1811.05849 [math.CO]) proved a structure theorem for tree-based phylogenetic networks and obtained linear-time and linear-delay algorithms for many basic problems on support trees, such as counting, optimisation, and enumeration. In the present paper, we consider the following fundamental problem in statistical data analysis: given a tree-based phylogenetic network $N$ whose arcs are associated with probability, create the top-$k$ support tree ranking for $N$ by their likelihood values. We provide a linear-delay (and hence optimal) algorithm for the problem and thus reveal the interesting property of tree-based phylogenetic networks that ranking top-$k$ support trees is as computationally easy as picking $k$ arbitrary support trees.

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