Skip to content
DraconiticResearch
Search Sources API
203,234 studies31 sourcesUpdated 45 min ago
Peer-reviewedCC BY-NC-ND 4.0Nature Communications

Fine-tuning of polygenic score to local data improves risk prediction and clinical implementation

  • Min Seo Kim
  • Yang Sui
  • Aniruddh P. Patel
  • So Mi Jemma Cho
  • Satoshi Koyama
  • Kaavya Paruchuri
  • Buu Truong
  • Injeong Shim
  • Minxian Wang
  • Fadi F. Bitar
  • Qiuli Chen
  • Patrick T. Ellinor
2 more authors
  • Pradeep Natarajan
  • Akl C. Fahed
Open at sourcePDFDOICite

Related

  1. From Monogenic Variants to Polygenic Risk Scores in Inherited Cardiomyopathies: Clinical Utility, Ancestry Gaps, and Future Implementation in Arab Populations
    GenesPeer-reviewedCC BYFull textGenetics & genomicsEurope PMC
  2. All of Us diversity and scale yield context-dependent improvements in polygenic prediction
    Kristin Tsuo, Zhuozheng Shi, Tian Ge +6
    Nature GeneticsPeer-reviewedLicence not stated24 citedGenetics & genomicsOpenAlex
  3. MI-PEFT: Mixture-of-Experts Integrated Parameter-Efficient Fine-Tuning Protein Language Models Improves Acidophilic Proteins Classification
    Honghan Shen
    arXivPreprintCC BY 4.0Full textBioinformatics & computational biologyarXiv
  4. Fine-tuning improves deep learning-based digital phenotyping of lettuce genetic resources
    Eunju Lee, Yuseok Jeong, Hyo Jun Bae +5
    Frontiers in Plant SciencePeer-reviewedCC BY 4.0Full textPlant biologyCrossrefEurope PMC
  5. BLocPRS: locus-aware ensembles of polygenic scores provide accurate linear prediction
    J. Song, S. Zabad, S. Gravel +1
    bioRxivPreprintCC BYFull textGenetics & genomicsbioRxiv

Cite

BibTeXRIS
BibTeX
@article{kim2026finetuning,
  title = {{Fine-tuning of polygenic score to local data improves risk prediction and clinical implementation}},
  author = {Min Seo Kim and Yang Sui and Aniruddh P. Patel and So Mi Jemma Cho and Satoshi Koyama and Kaavya Paruchuri and Buu Truong and Injeong Shim and Minxian Wang and Fadi F. Bitar and Qiuli Chen and Patrick T. Ellinor and Pradeep Natarajan and Akl C. Fahed},
  journal = {Nature Communications},
  year = {2026},
  month = oct,
  doi = {10.1038/s41467-026-77770-z},
  url = {https://www.nature.com/articles/s41467-026-77770-z},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - Fine-tuning of polygenic score to local data improves risk prediction and clinical implementation
AU  - Min Seo Kim
AU  - Yang Sui
AU  - Aniruddh P. Patel
AU  - So Mi Jemma Cho
AU  - Satoshi Koyama
AU  - Kaavya Paruchuri
AU  - Buu Truong
AU  - Injeong Shim
AU  - Minxian Wang
AU  - Fadi F. Bitar
AU  - Qiuli Chen
AU  - Patrick T. Ellinor
AU  - Pradeep Natarajan
AU  - Akl C. Fahed
PY  - 2026
DA  - 2026/10/23
JO  - Nature Communications
DO  - 10.1038/s41467-026-77770-z
UR  - https://www.nature.com/articles/s41467-026-77770-z
SN  - 2041-1723
ER  -