Constructing ancestral recombination graphs through reinforcement learning

RL is a promising and innovative approach to build ARGs. By learning to construct ARGs just from the data, our method differs from conventional methods that rely on heuristic rules or complex theoretical models.

Authors

Cédric Beaulac (ORCID: https://orcid.org/0000-0002-6050-5313)
Fabrice Larribe
Marie-Hélène Descary
Mélanie Raymond

Institutions

Université du Québec à Montréal (CA)

Publication Details

Journal: Frontiers in Genetics
Published: 2025-04-29
DOI: https://doi.org/10.3389/fgene.2025.1569358
Primary Topic: Evolutionary Algorithms and Applications
Type: article
Field-Weighted Citation Impact: 0.00

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article

Constructing ancestral recombination graphs through reinforcement learning

Cédric Beaulac, Fabrice Larribe, Marie-Hélène Descary, Mélanie Raymond

Apr 29, 2025

Frontiers in Genetics

Evolutionary Algorithms and Applications

article

Constructing ancestral recombination graphs through reinforcement learning

Cédric Beaulac, Fabrice Larribe, Marie-Hélène Descary, Mélanie Raymond

April 29, 2025article en

Abstract

Frontiers in GeneticsVol. 16

Université du Québec à Montréal (CA)

Openalex Percentile: Top 96%

Evolutionary Algorithms and Applications

DOI Open Access PDF OpenAlex

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Constructing ancestral recombination graphs through reinforcement learning — Cédric Beaulac, Fabrice Larribe, et al. · Frontiers in Genetics (2025) | TGRS Research Map | TGRS