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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| Autores principales: | , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| 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. |
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