| 标题 |
  Computational protein design 计算蛋白质设计
相关领域
蛋白质设计
合理设计
计算生物学
蛋白质表达
计算机科学
蛋白质结构
生物
生物化学
遗传学
基因
|
| 备注 |
作者Katherine I. Albanese, Sophie Barbe, Shunsuke Tagami, Derek N. Woolfson & Thomas Schiex
|
| 网址 | |
| DOI |
提醒：求助人提供的doi与AI识别不一致
10.1016/s0969-2126(99)80062-8
Doi
|
| 其它 | Combining molecular modelling, machine-learned models and an increasingly detailed understanding of protein chemistry and physics, computational protein design and human expertise have been able to produce new protein structures, assemblies and functions that do not exist in nature. Currently, generative deep-learning-based methods, which exploit large databases of protein sequences and structures, are revolutionizing the field, leading to new capabilities, improved reliability and democratized access in protein design. This Primer provides an introduction to the main approaches in computational protein design, covering both physics-based and machine-learning-based tools. It aims to be accessible to biological, physical and computer scientists alike. Emphasis is placed on understanding the practical challenges arising from limitations in our fundamental understanding of protein structure and function and on recent developments and new ideas that may help transcend these. |
| 求助人 | |
| 下载 | 该求助完结已超 24 小时，文件已从服务器自动删除，无法下载。 |
|
温馨提示：该文献已被科研通 学术中心 收录，前往查看
科研通『学术中心』是文献索引库，收集文献的基本信息（如标题、摘要、期刊、作者、被引量等），不提供下载功能。如需下载文献全文，请通过文献求助获取。
|
nozero
迷人秋烟
昏睡的蟠桃
迟大猫
科研小民工
shinysparrow
劲秉
SYLH
有何丿不可
默默地读文献
pcr163
maox1aoxin
cdercder
Singularity
热情的天蓝
子车茗
Grayball
YSM
邓佳鑫Alan
实验好难
皖公网安备34019202002308
