• Corpus ID: 233394505

Distinguishing Level-2 Phylogenetic Networks Using Phylogenetic Invariants

  title={Distinguishing Level-2 Phylogenetic Networks Using Phylogenetic Invariants},
  author={Muhammad Ardiyansyah},
In phylogenetics, it is important for the phylogenetic network model parameters to be identifiable so that the evolutionary histories of a group of species can be consistently inferred. However, as the complexity of the phylogenetic network models grows, the identifiability of network models becomes increasingly difficult to analyze. As an attempt to analyze the identifiability of network models, we check whether two networks are distinguishable. In this paper, we specifically study the… 
1 Citations

Classes of explicit phylogenetic networks and their biological and mathematical significance.

A thorough review of several subclasses of rooted phylogenetic networks (characterized by certain structural constraints) introduced in the literature, either to model specific biological phenomena or to enable tractable mathematical and computational analyses.



Counting phylogenetic networks of level 1 and 2.

This paper provides enumeration formulas (exact and asymptotic) for rooted and unrooted level-1 and level-2 phylogenetic networks with a given number of leaves and proves that the distribution of some parameters of these networks are asymPTotically normally distributed.

Comparison of Tree-Child Phylogenetic Networks

An injective representation of these networks as multisets of vectors of natural numbers, their path multiplicity vectors are provided, and this representation is used to define a distance on this class that extends the well-known Robinson-Foulds distance for phylogenetic trees and to give an alignment method for pairs of networks in this class.

Distinguishing level-1 phylogenetic networks on the basis of data generated by Markov processes

It is shown that the semi-directed network parameter of a triangle-free, level-1 network model with any fixed number of reticulation vertices is generically identifiable under the Jukes-Cantor, Kimura 2-parameter, or Kimura 3-parameters constraints.

Rooting for phylogenetic networks

It is shown that, in general, it is NP-hard to decide whether an undirected network can be oriented as a tree-based network.

The Structure of Level-k Phylogenetic Networks

The structure oflevel-k networks, and how they can be decomposed into level-k generators, is studied, and a polynomial time algorithm is provided which takes as input the set of level- k generators and builds theSet of level-(k + 1) generators.

Generation of Binary Tree-Child phylogenetic networks

This paper addresses the problem of generating all possible binary tree-child networks with a given number of leaves in an efficient way via reduction/augmentation operations that extend and generalize analogous operations for phylogenetic trees, and are biologically relevant.

Classes of tree-based networks

Recently, so-called tree-based phylogenetic networks have attracted considerable attention. These networks can be constructed from a phylogenetic tree, called the base tree, by adding additional

Distinguishing Phylogenetic Networks

Using tools from computational algebraic geometry, it is shown that the semi-directed network topology is generically identifiable for Jukes-Cantor large-cycle network models.

Reconstructibility of unrooted level-k phylogenetic networks from distances