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Random forest (RF) stands out as a highly favored machine learning approach for classification problems. The effectiveness of RF hinges on two key factors: the accuracy of individual trees and the diversity among them. In this study, we…

Machine Learning · Computer Science 2024-10-28 Ye-eun Kim , Seoung Yun Kim , Hyunjoong Kim

Probabilistic programming frameworks are powerful tools for statistical modelling and inference. They are not immediately generalisable to phylogenetic problems due to the particular computational properties of the phylogenetic tree object.…

Populations and Evolution · Quantitative Biology 2022-11-11 Christiaan Swanepoel , Mathieu Fourment , Xiang Ji , Hassan Nasif , Marc A Suchard , Frederick A Matsen , Alexei Drummond

The reconstruction of large phylogenetic trees from data that violates clocklike evolution (or as a supertree constructed from any m input trees) raises a difficult question for biologists - how can one assign relative dates to the vertices…

Combinatorics · Mathematics 2007-05-23 Tanja Gernhard , Daniel Ford , Rutger Vos , Mike Steel

Age estimation from facial images is typically cast as a nonlinear regression problem. The main challenge of this problem is the facial feature space w.r.t. ages is heterogeneous, due to the large variation in facial appearance across…

Computer Vision and Pattern Recognition · Computer Science 2017-12-21 Wei Shen , Yilu Guo , Yan Wang , Kai Zhao , Bo Wang , Alan Yuille

Phylogenetic networks are a generalization of phylogenetic trees that allow for the representation of evolutionary events acting at the population level, like recombination between genes, hybridization between lineages, and lateral gene…

Populations and Evolution · Quantitative Biology 2007-11-26 Gabriel Cardona , Francesc Rossello , Gabriel Valiente

We consider the problem of identifying jointly the ancestral sequence, the phylogeny and the parameters in models of DNA sequence evolution with insertion and deletion (indel). Under the classical TKF91 model of sequence evolution, we…

Populations and Evolution · Quantitative Biology 2024-11-15 Alex Xue , Brandon Legried , Wai-Tong Louis Fan

How can one analyze detailed 3D biological objects, such as neurons and botanical trees, that exhibit complex geometrical and topological variation? In this paper, we develop a novel mathematical framework for representing, comparing, and…

Machine Learning · Computer Science 2023-11-28 Guan Wang , Hamid Laga , Anuj Srivastava

Radiocarbon dating poses a challenge in many archaeological contexts due to the limited precision of conventional calibration methods. In this study, we introduce a novel approach to fine-dating that is based on the repeated application of…

Methodology · Statistics 2025-02-28 Sebastian Fürst

Life expectancy is a fundamental indicator of population health and socio-economic well-being, yet accurately forecasting it remains challenging due to the interplay of demographic, environmental, and healthcare factors. This study…

Machine Learning · Computer Science 2025-10-02 Roman Dolgopolyi , Ioanna Amaslidou , Agrippina Margaritou

Recent advances have allowed for both morphological fossil evidence and molecular sequences to be integrated into a single combined inference of divergence dates under the rule of Bayesian probability. In particular the fossilized…

Populations and Evolution · Quantitative Biology 2016-05-04 Alexei J. Drummond , Tanja Stadler

Recently, much attention has been given to understanding recombination events along a chromosome in a variety of field. For instance, many population genetics problems are limited by the inaccuracy of inferred evolutionary histories of…

Quantitative Methods · Quantitative Biology 2017-10-31 Jacqueline Kane , Joseph Rusinko , Katherine Thompson

Mean residual lifetime is an important measure utilized in various fields, including pharmaceutical companies, manufacturing companies, and insurance companies for survival analysis. However, the computation of mean residual lifetime can be…

Computation · Statistics 2025-09-30 Zekai Wang , Andrew Crawford , Ka Lok Lee , Lin Lu , Srihari Jaganathan

We have developed an alignment-free method that calculates phylogenetic distances using a maximum likelihood approach for a model of sequence change on patterns that are discovered in unaligned sequences. To evaluate the phylogenetic…

Quantitative Methods · Quantitative Biology 2007-05-23 Michael Höhl , Isidore Rigoutsos , Mark A. Ragan

Phylogenetic trees are widely used to understand the evolutionary history of organisms. Tree shapes provide information about macroevolutionary processes. However, macroevolutionary models are unreliable for inferring the true processes…

Populations and Evolution · Quantitative Biology 2021-10-11 Albert Ch. Soewongsono , Barbara R. Holland , Małgorzata M. O'Reilly

Phylogenetic reconstruction aims at finding plausible hypotheses of the evolutionary history of genes or species based on genomic sequence information. The distinction of orthologous genes (genes that having a common ancestry and diverged…

Populations and Evolution · Quantitative Biology 2016-02-29 Marc Hellmuth , Nicolas Wieseke

Phylogenetic trees are simple models of evolutionary processes. They describe conditionally independent divergent evolution of taxa from common ancestors. Phylogenetic trees commonly do not have enough flexibility to adequately model all…

Populations and Evolution · Quantitative Biology 2025-11-11 Jonathan D. Mitchell , Barbara R. Holland

Computational inference of dated evolutionary histories relies upon various hypotheses about RNA, DNA, and protein sequence mutation rates. Using mutation rates to infer these dated histories is referred to as molecular clock assumption.…

Populations and Evolution · Quantitative Biology 2021-01-11 Lena Collienne , Kieran Elmes , Mareike Fischer , David Bryant , Alex Gavryushkin

In this paper we propose a novel R package, called rsurv, developed for general survival data simulation purposes. The package is built under a new approach to simulate survival data that depends heavily on the use of dplyr verbs. The…

Computation · Statistics 2024-06-05 Fábio N. Demarqui

Random Forest (RF) is a powerful supervised learner and has been popularly used in many applications such as bioinformatics. In this work we propose the guided random forest (GRF) for feature selection. Similar to a feature selection method…

Machine Learning · Computer Science 2013-11-19 Houtao Deng

We investigate the use of additional 3D and phylogenetic non-3D tree balance indices for analyzing and monitoring forests using an exemplary "virtual forest" dataset from the Wytham Woods, Oxford, UK. This study assesses 3D model quality,…

Quantitative Methods · Quantitative Biology 2026-03-23 Sophie J. Kersting , Mareike Fischer