Machine-learning predicts genomic determinants of meiosis-driven structural variation in a eukaryotic pathogen

Structural variation in genomes of the same species is frequent but what drives the rearrangements remains unclear. Machine-learning of rearrangement patterns among telomere-to-telomere assemblies can accurately identify regions of intrinsic DNA instability in a eukaryotic pathogen.

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Detalles Bibliográficos
Autores principales: Thomas Badet, Simone Fouché, Fanny E. Hartmann, Marcello Zala, Daniel Croll
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/26805112d9a64392bfb163399db5f589
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Sumario:Structural variation in genomes of the same species is frequent but what drives the rearrangements remains unclear. Machine-learning of rearrangement patterns among telomere-to-telomere assemblies can accurately identify regions of intrinsic DNA instability in a eukaryotic pathogen.