计算机科学
数据科学
蛋白质设计
比例(比率)
编码(集合论)
蛋白质结构预测
源代码
蛋白质结构
生物
集合(抽象数据类型)
程序设计语言
生物化学
量子力学
物理
作者
Birte Höcker,Pinyan Lu,Anum Glasgow,Debora S. Marks,Pranam Chatterjee,Joanna S.G. Slusky,Ora Schueler‐Furman,P. G. Huang
出处
期刊:Cell systems
[Elsevier]
日期:2023-08-01
卷期号:14 (8): 629-632
标识
DOI:10.1016/j.cels.2023.07.005
摘要
It is important to make novel technologies easily accessible to non-expert users and provide guidance for their use. The protein design community openly shares methods, programs, and source code and has done so even before the AI (r)evolution. What changed is the scale and increased interest due to the improved precision in predictions. In fact, protein structures have already been predicted at large scale, and biologists can simply access them in the AlphaFold Protein Structure Database or ESM Metagenomic Atlas. Due to these incredibly useful resources, they do not even have to run the predictions themselves.
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