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Updated: Sep 10, 2025

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
07:15

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

Published on: January 16, 2019

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COVID-19の予後における遺伝的役割を理解するための機械学習アプローチ:炎症,ビタミンD,ACE2に関連する遺伝子ポリモルフィズムの影響

Sofía Jaurrieta-Largo1, José Pablo Miramontes-González2,3, Luis Corral-Gudino2,3

  • 1Department of Pneumonology, University Clinical Hospital of Valladolid, 47003 Valladolid, Spain.

International journal of molecular sciences
|August 28, 2025
PubMed
まとめ

遺伝的要因はCOVID-19の結果に大きな影響を与える. この研究では,重度のCOVID-19,肺炎,死亡リスクを予測する炎症およびビタミンD代謝に関連する重要な遺伝子ポリモルフィズムを特定しました.

キーワード:
ACE2 についてコロナウイルス遺伝学炎症機械学習ビタミンD

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