arXiv subjects

Yukihiro Murakami

Publications and source records attributed to Yukihiro Murakami.

25 records · Page 2Linked to original sources

arXiv2020

A Unifying Characterization of Tree-based Networks and Orchard Networks using Cherry Covers

Phylogenetic networks are used to study evolutionary relationships between species in biology. Such networks are often categorized into classes by their topological features, which stem from both biological and computational motivations. We study two network classes in this paper: tree-based networks and orchard networks. Tree-based networks are those that can be obtained by inserting edges between the edges of an underlying tree. Orchard networks are a recently introduced generalization of the class of tree-child networks. Structural characterizations have already been discovered for tree-based networks; this is not the case for orchard networks. In this paper, we introduce cherry covers---a unifying characterization of both network classes---in which we decompose the edges of the networks into so-called cherry shapes and reticulated cherry shapes. We show that cherry covers can be used to characterize the class of tree-based networks as well as the class of orchard networks. Moreover, we also generalize these results to non-binary networks.

math.CO↗

arXiv2020

On Cherry-picking and Network Containment

Phylogenetic networks are used to represent evolutionary scenarios in biology and linguistics. To find the most probable scenario, it may be necessary to compare candidate networks, to distinguish different networks, and to see when one network is contained in another. In this paper, we introduce cherry-picking networks, a class of networks that can be reduced by a sequence of two graph operations. We show that some networks are uniquely determined by the sequences that reduce them---we call these the reconstructible cherry-picking networks, and further show that given two cherry-picking networks within the same reconstructible class, one is contained in the other if a sequence for the latter network reduces the former network. By restricting our scope to tree-child networks, we show that the converse of the above statement holds, thereby showing that {\sc Network Containment}, the problem of checking whether a network is contained in another, can be solved in linear time for tree-child networks. We implement this algorithm in Python and show that the linear-time theoretical bound on the input size is achievable in practice. Lastly, we provide a linear time algorithm for deciding whether two tree-child networks are isomorphic.

math.CO↗

arXiv2020

Recognizing and realizing cactus metrics

The problem of realizing finite metric spaces in terms of weighted graphs has many applications. For example, the mathematical and computational properties of metrics that can be realized by trees have been well-studied and such research has laid the foundation of the reconstruction of phylogenetic trees from evolutionary distances. However, as trees may be too restrictive to accurately represent real-world data or phenomena, it is important to understand the relationship between more general graphs and distances. In this paper, we introduce a new type of metric called a cactus metric, that is, a metric that can be realized by a cactus graph. We show that, just as with tree metrics, a cactus metric has a unique optimal realization. In addition, we describe an algorithm that can recognize whether or not a metric is a cactus metric and, if so, compute its optimal realization in $O(n^3)$ time, where $n$ is the number of points in the space.

math.CO↗

arXiv2019

Combining Networks using Cherry Picking Sequences

Phylogenetic networks are important for the study of evolution. The number of methods to find such networks is increasing, but most such methods can only reconstruct small networks. To find bigger networks, one can attempt to combine small networks. In this paper, we study the {\sc Network Hybridization} problem, a problem of combining networks into another network with low complexity. We characterize this complexity via a restricted problem, {\sc Tree-child Network Hybridization}, and we present an FPT algorithm to efficiently solve this restricted problem.

cs.DM↗

arXiv2019

Polynomial-Time Algorithms for Phylogenetic Inference Problems involving duplication and reticulation

A common problem in phylogenetics is to try to infer a species phylogeny from gene trees. We consider different variants of this problem. The first variant, called Unrestricted Minimal Episodes Inference, aims at inferring a species tree based on a model with speciation and duplication where duplications are clustered in duplication episodes. The goal is to minimize the number of such episodes. The second variant, Parental Hybridization, aims at inferring a species \emph{network} based on a model with speciation and reticulation. The goal is to minimize the number of reticulation events. It is a variant of the well-studied Hybridization Number problem with a more generous view on which gene trees are consistent with a given species network. We show that these seemingly different problems are in fact closely related and can, surprisingly, both be solved in polynomial time, using a structure we call "beaded trees". However, we also show that methods based on these problems have to be used with care because the optimal species phylogenies always have a restricted form. To mitigate this problem, we introduce a new variant of Unrestricted Minimal Episodes Inference that minimizes the duplication episode depth. We prove that this new variant of the problem can also be solved in polynomial time

q-bio.PE↗

arXiv2019

Reconstructing Tree-Child Networks from Reticulate-Edge-Deleted Subnetworks

Network reconstruction lies at the heart of phylogenetic research. Two well studied classes of phylogenetic networks include tree-child networks and level-$k$ networks. In a tree-child network, every non-leaf node has a child that is a tree node or a leaf. In a level-$k$ network, the maximum number of reticulations contained in a biconnected component is $k$. Here, we show that level-$k$ tree-child networks are encoded by their reticulate-edge-deleted subnetworks, which are subnetworks obtained by deleting a single reticulation edge, if $k\geq 2$. Following this, we provide a polynomial-time algorithm for uniquely reconstructing such networks from their reticulate-edge-deleted subnetworks. Moreover, we show that this can even be done when considering subnetworks obtained by deleting one reticulation edge from each biconnected component with $k$ reticulations.

math.CO↗

arXiv2019

A Practical Fixed-Parameter Algorithm for Constructing Tree-Child Networks from Multiple Binary Trees

We present the first fixed-parameter algorithm for constructing a tree-child phylogenetic network that displays an arbitrary number of binary input trees and has the minimum number of reticulations among all such networks. The algorithm uses the recently introduced framework of cherry picking sequences and runs in $O((8k)^k \mathrm{poly}(n, t))$ time, where $n$ is the number of leaves of every tree, $t$ is the number of trees, and $k$ is the reticulation number of the constructed network. Moreover, we provide an efficient parallel implementation of the algorithm and show that it can deal with up to $100$ input trees on a standard desktop computer, thereby providing a major improvement over previous phylogenetic network construction methods.

cs.DM↗