Interpretable machine-learning prediction of PSEN1 missense variant pathogenicity based on multi-omics enrichment in six core Alzheimer's disease genes.
- DOI
- 10.1186/s13195-025-01950-0
- Published
- 2026 Jan 8
- Container
- Alzheimer's research & therapy
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1186/s13195-025-01950-0,
title = {Interpretable machine-learning prediction of PSEN1 missense variant pathogenicity based on multi-omics enrichment in six core Alzheimer's disease genes.},
author = {Yang D and Wang S and Lu Y and Zhu J and Chen J and Zhang B and Cai H and Teng B and Wei R and Cen Z and Luo W},
year = {2026},
journal = {Alzheimer's research \& therapy},
doi = {10.1186/s13195-025-01950-0},
url = {https://doi.org/10.1186/s13195-025-01950-0}
}RIS
TY - JOUR TI - Interpretable machine-learning prediction of PSEN1 missense variant pathogenicity based on multi-omics enrichment in six core Alzheimer's disease genes. AU - Yang D AU - Wang S AU - Lu Y AU - Zhu J AU - Chen J AU - Zhang B AU - Cai H AU - Teng B AU - Wei R AU - Cen Z AU - Luo W PY - 2026 JO - Alzheimer's research & therapy DO - 10.1186/s13195-025-01950-0 UR - https://doi.org/10.1186/s13195-025-01950-0 ER -
APA
D, Y., S, W., Y, L., J, Z., J, C., B, Z., H, C., B, T., R, W., Z, C., & W, L. (2026). Interpretable machine-learning prediction of PSEN1 missense variant pathogenicity based on multi-omics enrichment in six core Alzheimer's disease genes.. Alzheimer's research & therapy. https://doi.org/10.1186/s13195-025-01950-0
Source records
- pubmed · retrieved 2026-09-26T07:57:13.018Z