From memorization to generalization: Why physics will improve machine learning -based prediction of protein complexes
- DOI
- 10.1016/j.sbi.2026.103288
- Published
- 2026-06
- Container
- Current Opinion in Structural Biology
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.sbi.2026.103288,
title = {From memorization to generalization: Why physics will improve machine learning -based prediction of protein complexes},
author = {Ernest Glukhov and Sandor Vajda and Dima Kozakov},
year = {2026},
journal = {Current Opinion in Structural Biology},
doi = {10.1016/j.sbi.2026.103288},
url = {https://doi.org/10.1016/j.sbi.2026.103288}
}RIS
TY - JOUR TI - From memorization to generalization: Why physics will improve machine learning -based prediction of protein complexes AU - Ernest Glukhov AU - Sandor Vajda AU - Dima Kozakov PY - 2026 JO - Current Opinion in Structural Biology DO - 10.1016/j.sbi.2026.103288 UR - https://doi.org/10.1016/j.sbi.2026.103288 ER -
APA
Glukhov, E., Vajda, S., & Kozakov, D. (2026). From memorization to generalization: Why physics will improve machine learning -based prediction of protein complexes. Current Opinion in Structural Biology. https://doi.org/10.1016/j.sbi.2026.103288
Source records
- crossref · retrieved 2026-09-25T10:28:46.471Z