Machine learning-based prediction of memory requirements for metagenomic assembly in high-performance computing environments
- DOI
- 10.64898/2026.05.12.724571
- Published
- 2026-05-13
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- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.64898/2026.05.12.724571,
title = {Machine learning-based prediction of memory requirements for metagenomic assembly in high-performance computing environments},
author = {Sanchez S and Faack S and Beracochea M and Finn RD and Grüning B and Batut B and Zierep P.},
year = {2026},
doi = {10.64898/2026.05.12.724571},
url = {https://doi.org/10.64898/2026.05.12.724571}
}RIS
TY - JOUR TI - Machine learning-based prediction of memory requirements for metagenomic assembly in high-performance computing environments AU - Sanchez S AU - Faack S AU - Beracochea M AU - Finn RD AU - Grüning B AU - Batut B AU - Zierep P. PY - 2026 DO - 10.64898/2026.05.12.724571 UR - https://doi.org/10.64898/2026.05.12.724571 ER -
APA
S, S., S, F., M, B., RD, F., B, G., B, B., & P., Z. (2026). Machine learning-based prediction of memory requirements for metagenomic assembly in high-performance computing environments. https://doi.org/10.64898/2026.05.12.724571
Source records
- europe-pmc · retrieved 2026-09-25T14:39:42.910Z
- hal · retrieved 2026-09-25T14:39:42.971Z