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相关实验视频

Updated: Jul 11, 2025

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
05:08

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

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SuPreMo:使用基于序列的预测模型,简化in silico扰动的计算工具.

Ketrin Gjoni1,2, Katherine S Pollard1,2,3

  • 1Gladstone Institute of Data Science and Biotechnology, San Francisco, CA 94158, USA.

bioRxiv : the preprint server for biology
|November 14, 2023
PubMed
概括

预测模型的序列突变器 (SuPreMo) 能够在基因组中进行基因组编辑. 这个工具有助于优先考虑致病变体,并使用机器学习模型发现功能序列.

科学领域:

  • 基因组学就是基因组学.
  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学

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相关实验视频

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背景情况:

  • 计算基因组编辑至关重要,但面临着结构变异和数据输入要求的局限性.
  • 现有的方法很难确定导致功能影响的特定序列变化.

结论:

  • SuPreMo提供了一种用于in silico基因组序列操纵的综合解决方案.
  • 由SuPreMo生成的参考对和扰乱序列可以与机器学习模型集成.
  • 这种整合有助于优先考虑致病变体,并发现新的功能序列.