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Bayesian phylogenetics is vital for understanding evolutionary dynamics, and requires accurate and efficient approximation of posterior distributions over trees. In this work, we develop a variational Bayesian approach for ultrametric…

Machine Learning · Statistics 2026-02-16 Evan Sidrow , Alexandre Bouchard-Côté , Lloyd T. Elliott

We present two main contributions which help us in leveraging the theory of graphons for modeling evolutionary processes. We show a generative model for digraphons using a finite basis of subgraphs, which is representative of biological…

Machine Learning · Computer Science 2021-04-27 Abhinav Tamaskar , Bud Mishra

Typefaces are an essential resource employed by graphic designers. The increasing demand for innovative type design work increases the need for good technological means to assist the designer in the creation of a typeface. We present an…

Neural and Evolutionary Computing · Computer Science 2018-06-27 Tiago Martins , João Correia , Ernesto Costa , Penousal Machado

We are facing a real challenge when coping with the continuous acceleration of scientific production and the increasingly changing nature of science. In this article, we extend the classical framework of co-word analysis to the study of…

Physics and Society · Physics 2015-03-13 David Chavalarias , Jean-Philippe Cointet

Fossil-based palaeoclimate reconstruction is an important area of ecological science that has gained momentum in the backdrop of the global climate change debate. The hierarchical Bayesian paradigm provides an interesting platform for…

Applications · Statistics 2013-12-13 Sabyasachi Mukhopadhyay , Sourabh Bhattacharya

Parameter sweeping is a widely used algorithmic technique in computational science. It is specially suited for high-throughput computing since the jobs evaluating the parameter space are loosely coupled or independent. A tool that…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-05-18 Alejandro Lorca , Eduardo Huedo , Ignacio M. Llorente

Identifying and understanding the large-scale biodiversity patterns in time and space is vital for conservation and addressing fundamental ecological and evolutionary questions. Network-based methods have proven useful for simplifying and…

Populations and Evolution · Quantitative Biology 2023-07-03 Daniel Edler , Anton Holmgren , Alexis Rojas , Joaquín Calatayud , Martin Rosvall , Alexandre Antonelli

Phylogenetic trees are pervasively used to depict evolutionary relationships. Increasingly, researchers need to visualize large trees and compare multiple large trees inferred for the same set of taxa (reflecting uncertainty in the tree…

Populations and Evolution · Quantitative Biology 2016-04-21 Oscar Robinson , David Dylus , Christophe Dessimoz

Tumor cells acquire different genetic alterations during the course of evolution in cancer patients. As a result of competition and selection, only a few subgroups of cells with distinct genotypes survive. These subgroups of cells are often…

Applications · Statistics 2018-03-20 Li Zeng , Joshua L. Warren , Hongyu Zhao

Here we introduce a new design framework for synthetic biology that exploits the advantages of Bayesian model selection. We will argue that the difference between inference and design is that in the former we try to reconstruct the system…

Molecular Networks · Quantitative Biology 2015-05-27 Chris Barnes , Daniel Silk , Xia Sheng , Michael P. H. Stumpf

We propose a novel method for the inference of phylogenetic trees that utilises point configurations on hyperbolic space as its optimisation landscape. Each taxon corresponds to a point of the point configuration, while the evolutionary…

Machine Learning · Computer Science 2021-06-07 Benjamin Wilson

Evolutionary sparse learning (ESL) uses a supervised machine learning approach, Least Absolute Shrinkage and Selection Operator (LASSO), to build models explaining the relationship between a hypothesis and the variation across genomic…

Populations and Evolution · Quantitative Biology 2025-01-10 Maxwell Sanderford , Sudip Sharma , Glen Stecher , Jun Liu , Jieping Ye , Sudhir Kumar

Directional data emerges in a wide array of applications, ranging from atmospheric sciences to medical imaging. Modeling such data, however, poses unique challenges by virtue of their being constrained to non-Euclidean spaces like…

Statistics Theory · Mathematics 2019-07-10 Subhadip Pal , Subhajit Sengupta , Riten Mitra , Arunava Banerjee

The evolution of molecular and phenotypic traits is commonly modelled using Markov processes along a phylogeny. This phylogeny can be a tree, or a network if it includes reticulations, representing events such as hybridization or admixture.…

Populations and Evolution · Quantitative Biology 2024-08-28 Benjamin Teo , Paul Bastide , Cécile Ané

Predicting the next activity of a running process is an important aspect of process management. Recently, artificial neural networks, so called deep-learning approaches, have been proposed to address this challenge. This demo paper…

Machine Learning · Computer Science 2017-05-04 Joerg Evermann , Jana-Rebecca Rehse , Peter Fettke

Phylogenetic inference can potentially result in a more accurate tree using data from multiple loci. However, if the loci are incongruent--due to events such as incomplete lineage sorting or horizontal gene transfer--it can be misleading to…

Populations and Evolution · Quantitative Biology 2016-03-10 Kevin Gori , Tomasz Suchan , Nadir Alvarez , Nick Goldman , Christophe Dessimoz

Phylogenetic inference, the task of reconstructing how related sequences evolved from common ancestors, is a central objective in evolutionary genomics. The current state-of-the-art methods exploit probabilistic models of sequence evolution…

Populations and Evolution · Quantitative Biology 2026-02-19 Luc Blassel , Noémie Sauvage , Pierre Barrat-Charlaix , Bastien Boussau , Nicolas Lartillot , Laurent Jacob

Single-step retrosynthesis aims to predict a set of reactions that lead to the creation of a target molecule, which is a crucial task in molecular discovery. Although a target molecule can often be synthesized with multiple different…

Machine Learning · Computer Science 2025-04-15 Piotr Gaiński , Michał Koziarski , Krzysztof Maziarz , Marwin Segler , Jacek Tabor , Marek Śmieja

In the past decade, transcriptome data have become an important component of many phylogenetic studies. Phylogenetic studies now regularly include genes from newly sequenced transcriptomes, as well as publicly available transcriptomes and…

Genomics · Quantitative Biology 2014-01-14 Casey W. Dunn , Mark Howison , Felipe Zapata

Comparative and evolutive ecologists are interested in the distribution of quantitative traits among related species. The classical framework for these distributions consists of a random process running along the branches of a phylogenetic…

Applications · Statistics 2017-08-24 Paul Bastide , Mahendra Mariadassou , Stéphane Robin