对于蛋白质-蛋白质相互作用分析的深度学习的最新进展:综合性审查
1School of Electrical and Electronics Engineering, Chung-Ang University, Seoul 06974, Republic of Korea.
Molecules (Basel, Switzerland)
|July 14, 2023
概括
深度学习正在通过加速蛋白质-蛋白质相互作用 (PPI) 的研究来彻底改变计算生物学. 本综述分析了PPI分析的深度学习的最新进展,帮助研究人员在这个充满活力的领域.
科学领域:
- 计算生物学 计算生物学
- 人工智能的人工智能
- 生物信息学是一种生物信息学.
背景情况:
- 蛋白与蛋白相互作用 (PPI) 是生物过程的基础.
- 了解PPI对于破译生物系统和开发治疗方法至关重要.
- 深度学习 (AI) 越来越多地用于分析复杂的生物数据.
研究的目的:
- 为PPI分析应用的深度学习方法提供全面的审查.
- 从2021-2023年开始,批判性地评估该领域的新发展.
- 为研究人员在PPI分析中使用深度学习作为参考.
主要方法:
- 对2021年至2023年间发表的研究的文献综述.
- 在PPI分析中使用的尖端深度学习技术的分析.
- 综合了最近的进展和趋势.
主要成果:
- 在PPI分析中发现了深度学习应用的扩散.
- 突出了当前使用的关键深度学习方法.
- 展示了该领域的快速发展.
结论:
- 深度学习是PPI分析的计算生物学中的一个变革性工具.
- 这一综述巩固了最近的进展,帮助研究人员了解当前的趋势.
- 这些发现提供了关于人工智能和PPI研究之间的协同关系的见解.
关键词:
在这里,我们可以看到AIAIAI.在PPI预测预测.人工智能的人工智能是人工智能.生物信息学是一种生物信息学.计算生物学是计算生物学.深度学习是一种深度学习.机器学习是机器学习.蛋白质网络是一种蛋白质网络.蛋白质蛋白质相互作用更多相关视频
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