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We propose a stochastic model for evolution. Births and deaths of species occur with constant probabilities. Each new species is associated with a fitness sampled from the uniform distribution on [0,1]. Every time there is a death event…

Probability · Mathematics 2010-11-09 Herve Guiol , Fabio P. Machado , Rinaldo B. Schinazi

Phylogenetic diversity is a measure for describing how much of an evolutionary tree is spanned by a subset of species. If one applies this to the (unknown) subset of current species that will still be present at some future time, then this…

Subcellular Processes · Quantitative Biology 2009-09-29 Beata Faller , Fabio Pardi , Mike Steel

Possibility to establish macroscopic phenomenological theory for biological systems, akin to the akin to the well-established framework of thermodynamics, is briefly reviewed. We introduce the concept of an evolutionary fluctuation-response…

Biological Physics · Physics 2024-01-11 Kunihiko Kaneko

We consider the problem of determining the time evolution of a trait distribution in a mathematical model of non-uniform populations with parametric heterogeneity. This means that we consider only heterogeneous populations in which…

Populations and Evolution · Quantitative Biology 2018-09-25 Georgy P. Karev , Artem S. Novozhilov

Null models of binary phylogenetic trees are useful for testing hypotheses on real world phylogenies. In this paper we consider phylogenies as binary trees without edge lengths together with a sampling measure and encode them as algebraic…

Probability · Mathematics 2020-06-17 Josué Nussbaumer , Anita Winter

We study a version of the Tangled Nature model of evolutionary ecology redefined in a phenotype space where mutants have properties correlated to their parents. The model has individual-based dynamics whilst incorporating species scale…

Populations and Evolution · Quantitative Biology 2016-09-08 Simon Laird , Henrik Jeldtoft Jensen

Simple stochastic models for phylogenetic trees on species have been well studied. But much paleontology data concerns time series or trees on higher-order taxa, and any broad picture of relationships between extant groups requires use of…

Populations and Evolution · Quantitative Biology 2007-08-28 David Aldous , Maxim Krikun , Lea Popovic

The formation of opinions in a large population is governed by endogenous (human interactions) and exogenous (media influence) factors. In the analysis of opinion evolution in a large population, decision making rules can be approximated…

Dynamical Systems · Mathematics 2012-05-08 Anahita Mirtabatabaei , Peng Jia , Francesco Bullo

A phylogenetic tree shows the evolutionary relationships among species. Internal nodes of the tree represent speciation events and leaf nodes correspond to species. A goal of phylogenetics is to combine such trees into larger trees, called…

Artificial Intelligence · Computer Science 2014-01-16 Neil C. A. Moore , Patrick Prosser

We consider the goodness of fit testing problem for linear stochastic differential equation (Ornstein-Uhlenbeck process). The basic hypothesis is supposed to be composite with two-dimensional unknown parameter. We study two goodness of fit…

Statistics Theory · Mathematics 2013-05-16 Yury A. Kutoyants

As whole genomes become widely available, maximum likelihood and Bayesian phylogenetic methods are demonstrating their limits in meeting the escalating computational demands. Conversely, distance-based phylogenetic methods are efficient,…

Populations and Evolution · Quantitative Biology 2025-02-07 Matthew J. Penn , Neil Scheidwasser , Mark P. Khurana , Christl A. Donnelly , David A. Duchêne , Samir Bhatt

We show that $n$-variable tree-structured Ising models can be learned computationally-efficiently to within total variation distance $\epsilon$ from an optimal $O(n \ln n/\epsilon^2)$ samples, where $O(\cdot)$ hides an absolute constant…

Machine Learning · Computer Science 2020-12-01 Constantinos Daskalakis , Qinxuan Pan

Identifiability of evolutionary tree models has been a recent topic of discussion and some models have been shown to be non-identifiable. A coalescent-based rooted population tree model, originally proposed by Nielsen et al. 1998 [2], has…

Populations and Evolution · Quantitative Biology 2013-04-15 Arindam RoyChoudhury

Many biological studies involve inferring the evolutionary history of a sample of individuals from a large population and interpreting the reconstructed tree. Such an ascertained tree typically represents only a small part of a…

Populations and Evolution · Quantitative Biology 2024-08-13 Michael Celentano , William S. DeWitt , Sebastian Prillo , Yun S. Song

The central goal of a dynamical theory of evolution is to abstract the mean evolutionary trajectory in the trait space by considering ecological processes at the level of the individual. In this work, we develop such a theory for a new…

Populations and Evolution · Quantitative Biology 2020-03-25 Vaibhav Madhok

The general Markov model of the evolution of biological sequences along a tree leads to a parameterization of an algebraic variety. Understanding this variety and the polynomials, called phylogenetic invariants, which vanish on it, is a…

Algebraic Geometry · Mathematics 2007-06-13 Elizabeth S. Allman , John A. Rhodes

Inferring dependencies between complex biological traits while accounting for evolutionary relationships between specimens is of great scientific interest yet remains infeasible when trait and specimen counts grow large. The…

We consider the accumulation of beneficial and deleterious mutations in large asexual populations. The rate of adaptation is affected by the total mutation rate, proportion of beneficial mutations and population size $N$. We show that…

Probability · Mathematics 2010-10-18 Feng Yu , Alison Etheridge , Charles Cuthbertson

A prediction interval covers a future observation from a random process in repeated sampling, and is typically constructed by identifying a pivotal quantity that is also an ancillary statistic. Analogously, a tolerance interval covers a…

Methodology · Statistics 2022-01-19 Geoffrey S Johnson

Over the past decades, researchers and ML practitioners have come up with better and better ways to build, understand and improve the quality of ML models, but mostly under the key assumption that the training data is distributed…

Machine Learning · Computer Science 2019-10-14 Yeounoh Chung , Peter J. Haas , Eli Upfal , Tim Kraska
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