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Survival analysis concerns the task of predicting the time until an event occurs. Often used in the medical field, survival analysis deals with incomplete (i.e., censored) data, for instance, from patients who did not experience the event…

Machine Learning · Computer Science 2026-05-29 Thalea Schlender , Peter A. N. Bosman , Tanja Alderliesten

In this paper, we present a novel approach to accelerate the Bayesian inference process, focusing specifically on the nested sampling algorithms. Bayesian inference plays a crucial role in cosmological parameter estimation, providing a…

Instrumentation and Methods for Astrophysics · Physics 2024-10-17 Isidro Gómez-Vargas , J. Alberto Vázquez

Stochastic mapping is a simulation-based method for probabilistically mapping substitution histories onto phylogenies according to continuous-time Markov models of evolution. This technique can be used to infer properties of the…

Computation · Statistics 2017-02-10 Amrit Dhar , Vladimir N. Minin

This paper characterizes and discusses devolutionary genetic algorithms and evaluates their performances in solving the minimum labeling Steiner tree (MLST) problem. We define devolutionary algorithms as the process of reaching a feasible…

Optimization and Control · Mathematics 2020-04-22 Nassim Dehouche

A method to control results of gradient descent unsupervised learning in a deep neural network by using evolutionary algorithm is proposed. To process crossover of unsupervisedly trained models, the algorithm evaluates pointwise fitness of…

Machine Learning · Statistics 2018-03-29 Takeshi Inagaki

Data subsampling has become widely recognized as a tool to overcome computational and economic bottlenecks in analyzing massive datasets. We contribute to the development of adaptive design for estimation of finite population…

Methodology · Statistics 2024-07-08 Henrik Imberg , Xiaomi Yang , Carol Flannagan , Jonas Bärgman

With this paper, we contribute to the growing research area of feature-based analysis of bio-inspired computing. In this research area, problem instances are classified according to different features of the underlying problem in terms of…

Neural and Evolutionary Computing · Computer Science 2016-02-10 Shayan Poursoltan , Frank Neumann

Gene gain-loss-duplication models are commonly based on continuous-time birth-death processes. Employed in a phylogenetic context, such models have been increasingly popular in studies of gene content evolution across multiple genomes.…

Populations and Evolution · Quantitative Biology 2021-07-27 Miklos Csuros

Summary: GeneSupport implements a genome-scale algorithm: Maximum Gene-Support Tree to estimate species tree from gene trees based on multilocus sequences. It provides a new option for multiple genes to infer species tree. It is…

Genomics · Quantitative Biology 2009-10-13 Yunfeng Shan , Xiu-Qing Li

Phylogeny is the field of modelling the temporal discrete dynamics of speciation. Complex models can nowadays be studied using the Approximate Bayesian Computation approach which avoids likelihood calculations. The field's progression is…

Populations and Evolution · Quantitative Biology 2020-11-23 Krzysztof Bartoszek , Pietro Liò

In evolutionary computation, it is commonly assumed that a search algorithm acquires knowledge about a problem instance by sampling solutions from the search space and evaluating them with a fitness function. This is necessarily inefficient…

Neural and Evolutionary Computing · Computer Science 2024-11-12 Piotr Wyrwiński , Krzysztof Krawiec

In this paper we present a novel tool to evaluate problem solving systems. Instead of using a system to solve a problem, we suggest using the problem to evaluate the system. By finding a numerical representation of a problem's complexity,…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Goren Gordon , Uri Einziger-Lowicz

The ongoing explosion of genome sequence data is transforming how we reconstruct and understand the histories of biological systems. Across biological scales, from individual cells to populations and species, trees-based models provide a…

Populations and Evolution · Quantitative Biology 2025-12-08 Yun Deng , Shing H. Zhan , Yulin Zhang , Chao Zhang , Bingjie Chen

The way to infer well-supported phylogenetic trees that precisely reflect the evolutionary process is a challenging task that completely depends on the way the related core genes have been found. In previous computational biology studies,…

Discovering evolutionary traits that are heritable across species on the tree of life (also referred to as a phylogenetic tree) is of great interest to biologists to understand how organisms diversify and evolve. However, the measurement of…

Phylogenetic comparative analysis is an approach to inferring evolutionary process from a combination of phylogenetic and phenotypic data. The last few years have seen increasingly sophisticated models employed in the evaluation of more and…

Populations and Evolution · Quantitative Biology 2021-05-27 Clayton E. Cressler , Marguerite A. Butler , Aaron A. King

To understand biological diversification, it is important to account for large-scale processes that affect the evolutionary history of groups of co-distributed populations of organisms. Such events predict temporally clustered divergences…

Populations and Evolution · Quantitative Biology 2014-08-11 Jamie R. Oaks

As researchers collect increasingly large molecular data sets to reconstruct the Tree of Life, the heterogeneity of signals in the genomes of diverse organisms poses challenges for traditional phylogenetic analysis. A class of phylogenetic…

Populations and Evolution · Quantitative Biology 2015-09-11 Liang Liu , Zhenxiang Xi , Shaoyuan Wu , Charles Davis , Scott V. Edwards

An evolutionary search space can be smoothly transformed via a suitable change of basis; however, it can be difficult to determine an appropriate basis. In this paper, a method is proposed to select an optimum basis can be used to simplify…

Neural and Evolutionary Computing · Computer Science 2019-04-22 Junghwan Lee , Yong-Hyuk Kim

Generative models derived from large protein sequence alignments define complex fitness landscapes, but their utility for accurately modeling non-equilibrium evolutionary dynamics remains unclear. In this work, we perform a rigorous…

Populations and Evolution · Quantitative Biology 2026-02-10 Leonardo Di Bari , Thierry Mora , Andrea Pagnani , Aleksandra M. Walczak , Francesco Zamponi , Saverio Rossi