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Understanding the complex interactions within the microbiome is crucial for developing effective diagnostic and therapeutic strategies. Traditional machine learning models often lack interpretability, which is essential for clinical and…

Machine Learning · Computer Science 2024-10-22 Swagatam Haldar , Christoph Stein-Thoeringer , Vadim Borisov

We present convincing empirical evidence for an effective and general strategy for building accurate small models. Such models are attractive for interpretability and also find use in resource-constrained environments. The strategy is to…

Machine Learning · Computer Science 2024-04-30 Abhishek Ghose

Spatially-explicit estimates of population density, together with appropriate estimates of uncertainty, are required in many management contexts. Density Surface Models (DSMs) are a two-stage approach for estimating spatially-varying…

Methodology · Statistics 2021-02-25 Mark V Bravington , David L Miller , Sharon L Hedley

Computer simulations are an important tool for studying the mechanics of biological evolution. In particular, in silico work with agent-based models provides an opportunity to collect high-quality records of ancestry relationships among…

Neural and Evolutionary Computing · Computer Science 2024-10-03 Matthew Andres Moreno , Anika Ranjan , Emily Dolson , Luis Zaman

Determining the relative importance of environmental factors, biotic interactions and stochasticity in assembling and maintaining species-rich communities remains a major challenge in ecology. In plant communities, interactions between…

Populations and Evolution · Quantitative Biology 2018-03-20 T. Rajala , S. Olhede , D. J. Murrell

Diversity indices are useful single-number metrics for characterizing a complex distribution of a set of attributes across a population of interest. The utility of these different metrics or sets of metrics depend on the context and…

Populations and Evolution · Quantitative Biology 2020-03-06 Song Xu , Lucas Böttcher , Tom Chou

The behavior of ecological systems mainly relies on the interactions between the species it involves. We consider the problem of inferring the species interaction network from abundance data. To be relevant, any network inference…

Applications · Statistics 2019-10-29 Raphaëlle Momal , Stéphane Robin , Christophe Ambroise

Given an unknown dynamical system, what is the minimum number of samples needed for effective learning of its governing laws and accurate prediction of its future evolution behavior, and how to select these critical samples? In this work,…

Machine Learning · Computer Science 2024-01-15 Ce Zhang , Kailiang Wu , Zhihai He

For taxonomic levels higher than species, the abundance distributions of number of subtaxa per taxon tend to approximate power laws, but often show strong deviationns from such a law. Previously, these deviations were attributed to…

Biological Physics · Physics 2009-11-06 Johan Chu , Chris Adami

A method was developed for Bayesian inference of species phylogeny using the multi-species coalescent model. To improve the mixing properties of the Markov chain Monte Carlo (MCMC) algorithm that traverses the space of species trees, we…

Populations and Evolution · Quantitative Biology 2015-12-15 Bruce Rannala , Ziheng Yang

Entropy is a measure of heterogeneity widely used in applied sciences, often when data are collected over space. Recently, a number of approaches has been proposed to include spatial information in entropy. The aim of entropy is to…

Statistics Theory · Mathematics 2019-11-12 Linda Altieri , Daniela Cocchi , Giulia Roli

Sequence comparison across multiple organisms aids in the detection of regions under selection. However, resource limitations require a prioritization of genomes to be sequenced. This prioritization should be grounded in two considerations:…

Genomics · Quantitative Biology 2007-05-23 Jon D. McAuliffe , Michael I. Jordan , Lior Pachter

Abundance data are used in ecology for species monitoring and conservation. These count data often display several specific characteristics like numerous missing data, high variance, and a high proportion of zeros, particularly when…

Continuous space species distribution models (SDMs) have a long-standing history as a valuable tool in ecological statistical analysis. Geostatistical and preferential models are both common models in ecology. Geostatistical models are…

Applications · Statistics 2023-07-17 Mario Figueira , David Conesa , Antonio López-Quílez , Iosu Paradinas

Inferring concerted changes among biological traits along an evolutionary history remains an important yet challenging problem. Besides adjusting for spurious correlation induced from the shared history, the task also requires sufficient…

Motivated by the fundamental problem of measuring species diversity, this paper introduces the concept of a cluster structure to define an exchangeable cluster probability function that governs the joint distribution of a random count and…

Methodology · Statistics 2014-10-14 Mingyuan Zhou , Stephen G Walker

We consider the estimation of densities in multiple subpopulations, where the available sample size in each subpopulation greatly varies. This problem occurs in epidemiology, for example, where different diseases may share similar…

Methodology · Statistics 2021-09-15 Jiaming Qiu , Xiongtao Dai , Zhengyuan Zhu

Connecting galaxies with their descendants (or progenitors) at different redshifts can yield strong constraints on galaxy evolution. Observational studies have historically selected samples of galaxies using a physical quantity, such as…

Astrophysics of Galaxies · Physics 2015-05-20 Carl J. Mundy , Christopher J. Conselice , Jamie R. Ownsworth

The number of extant individuals within a lineage, as exemplified by counts of species numbers across genera in a higher taxonomic category, is known to be a highly skewed distribution. Because the sublineages (such as genera in a clade)…

Applications · Statistics 2009-01-09 Panagis Moschopoulos , Max Shpak

Adequate sampling is essential for the well-functioning of a market surveillance system. As small as possible statistically significant sample size is the main factor that determines the costs of market surveillance actions. This paper…

Applications · Statistics 2019-11-06 Ivan Hendrikx , Nikola Tuneski