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Related papers: Measure representation of evolving genealogies

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In a series of recent works it has been shown that a class of simple models of evolving populations under selection leads to genealogical trees whose statistics are given by the Bolthausen-Sznitman coalescent rather than by the well known…

Disordered Systems and Neural Networks · Physics 2015-05-28 Éric Brunet , Bernard Derrida

We examine the question of existence and uniqueness of evolution systems of measures for non-autonomous Ornstein-Uhlenbeck-type processes with jumps. In particular, we give examples where we explicitly compute the densities of such families…

Probability · Mathematics 2012-05-07 Robert Wooster

The time evolution of complex systems usually can be described through stochastic processes. These processes are measured at finite resolution, what necessarily reduces them to finite sequences of real numbers. In order to relate these data…

Condensed Matter · Physics 2007-05-23 D. M. Tavares , L. S. Lucena

The concepts of orthology, paralogy, and xenology play a key role in molecular evolution. Orthology and paralogy distinguish whether a pair of genes originated by speciation or duplication. The corresponding binary relations on a set of…

Discrete Mathematics · Computer Science 2016-03-09 Marc Hellmuth , Peter F. Stadler , Nicolas Wieseke

We study the evolution of a particle system whose genealogy is given by a supercritical continuous time Galton--Watson tree. The particles move independently according to a Markov process and when a branching event occurs, the offspring…

Probability · Mathematics 2012-02-20 Vincent Bansaye , Jean-François Delmas , Laurence Marsalle , Viet Chi Tran

In [Aldous,Pitman,1998] a tree-valued Markov chain is derived by pruning off more and more subtrees along the edges of a Galton-Watson tree. More recently, in [Abraham,Delmas,2012], a continuous analogue of the tree-valued pruning dynamics…

Probability · Mathematics 2015-11-26 Wolfgang Löhr , Guillaume Voisin , Anita Winter

Genetic Programming (GP) is an evolutionary algorithm commonly used for machine learning tasks. In this paper we present a method that allows GP to transform the representation of a large-scale machine learning dataset into a more compact…

Neural and Evolutionary Computing · Computer Science 2018-02-21 Lino Rodriguez-Coayahuitl , Alicia Morales-Reyes , Hugo Jair Escalante

Evolution has fascinated quantitative and physical scientists for decades: how can the random process of mutation, recombination, and duplication of genetic information generate the diversity of life? What determines the rate of evolution?…

Populations and Evolution · Quantitative Biology 2018-04-23 Richard A. Neher , Aleksandra M. Walczak

If we follow an asexually reproducing population through time, then the amount of time that has passed since the most recent common ancestor (MRCA) of all current individuals lived will change as time progresses. The resulting "MRCA age"…

Probability · Mathematics 2010-01-13 Steven N. Evans , Peter L. Ralph

In lifelong learning, tasks (or classes) to be learned arrive sequentially over time in arbitrary order. During training, knowledge from previous tasks can be captured and transferred to subsequent ones to improve sample efficiency. We…

Machine Learning · Computer Science 2022-03-02 Xinyuan Cao , Weiyang Liu , Santosh S. Vempala

Recent advances in high-throughput genomics technologies have resulted in the sequencing of large numbers of (near) complete genomes. These genome sequences are being mined for important functional elements, such as genes. They are also…

Genomics · Quantitative Biology 2007-05-23 Lior Pachter

We study the conditions under which the isometry of spaces with metrics generated by weights given on the edges of finite trees is equivalent to the isomorphism of these trees. Similar questions are studied for ultrametric spaces generated…

Metric Geometry · Mathematics 2020-02-18 Oleksiy Dovgoshey

Graphs are interesting structures: extremely useful to depict real-life problems, extremely easy to understand given a sketch, extremely complicated to represent formally, extremely complicated to compare. Phylogeny is the study of the…

Data Structures and Algorithms · Computer Science 2019-01-18 Bernardo Lopo Tavares

Learning informative representations of phylogenetic tree structures is essential for analyzing evolutionary relationships. Classical distance-based methods have been widely used to project phylogenetic trees into Euclidean space, but they…

Machine Learning · Statistics 2025-02-10 Tianyu Xie , Harry Richman , Jiansi Gao , Frederick A. Matsen , Cheng Zhang

Motivated by the problem of maintaining data structures for a large sets of points that are evolving over the course of time, we consider the problem of maintaining a set of labels assigned to the vertices of a tree, where the locations of…

Data Structures and Algorithms · Computer Science 2022-08-24 Aditya Acharya , David M. Mount

Coalescent processes, including mutation, are derived from Moran type population models admitting large offspring numbers. Including mutation in the coalescent process allows for quantifying the turnover of alleles by computing the…

Populations and Evolution · Quantitative Biology 2012-12-11 Bjarki Eldon

Phylogenetic inference-the derivation of a hypothesis for the common evolutionary history of a group of species- is an active area of research at the intersection of biology, computer science, mathematics, and statistics. One assumes the…

Populations and Evolution · Quantitative Biology 2016-06-21 Ruth Davidson , Joseph Rusinko , Zoe Vernon , Jing Xi

We code Galton-Walton trees by a continuous height process, in order to give a precise meaning to the convergence of forests of trees. This allows us to establish the convergence of the forest of genealogical trees of the branching process…

Probability · Mathematics 2020-03-12 Ibrahima Drame

We observe $n$ sequences at each of $m$ sites, and assume that they have evolved from an ancestral sequence that forms the root of a binary tree of known topology and branch lengths, but the sequence states at internal nodes are unknown.…

Computation · Statistics 2014-08-28 Adam Persing , Ajay Jasra , Alexandros Beskos , David Balding , Maria De Iorio

Complex networks, modeled as large graphs, received much attention during these last years. However, data on such networks is only available through intricate measurement procedures. Until recently, most studies assumed that these…

Networking and Internet Architecture · Computer Science 2007-05-23 Matthieu Latapy , Clemence Magnien