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Updated: Jul 5, 2025

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila
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Published on: August 20, 2019

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西格玛利用蛋白质结构信息来预测误解变异的病原性

Hengqiang Zhao1, Huakang Du1, Sen Zhao1

  • 1Department of Orthopedic Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China; Beijing Key Laboratory for Genetic Research of Skeletal Deformity, Beijing 100730, China.

Cell reports methods
|January 11, 2024
PubMed
概括

我们开发了SIGMA,这是一种使用蛋白质结构预测来评估误解变体致病性的新工具. 在SIGMA+中与其他预测器相结合,SIGMA在识别引起疾病的基因突变方面表现出卓越的准确性.

关键词:
科普:遗传学 在CP:遗传学.CP:系统生物学 系统生物学机器学习是机器学习.错误的意义的变体蛋白质结构 蛋白质结构变量效应预测器变量效应预测器

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