Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Genetic Screens02:46

Genetic Screens

Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which result in visible changes...
Drug Discovery: Overview01:26

Drug Discovery: Overview

Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Deep Learning and Machine Learning Modeling Identifies Thidiazuron as a Key Modulator of Somatic Embryogenesis and Shoot Organogenesis in <i>Ferula assa-foetida</i> L.

Biology·2025
Same author

Lightweight Vision Transformer with transfer learning for interpretable Alzheimer's disease severity assessment.

Scientific reports·2025
Same author

Differential Roles of Neuro-Inflammatory Regulator, MAPK11 in Cortex and Hippocampus Following Post-Stroke Cognitive Impairments in Rats.

Journal of neuroimmune pharmacology : the official journal of the Society on NeuroImmune Pharmacology·2025
Same author

Investigating RND efflux pumps in <i>Sphingobium yanoikuyae</i> P4: the role of nonpathogenic bacteria in antibiotic resistance gene spread amid environmental contamination.

Journal of biomolecular structure & dynamics·2025
Same author

Machine intelligence-driven framework for optimized hit selection in virtual screening.

Journal of cheminformatics·2022

相关实验视频

Updated: Jun 30, 2026

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.8K

机器智能驱动的虚拟选方法对大数据的进步.

Neeraj Kumar1,2, Vishal Acharya1,2

  • 1Artificial Intelligence for Computational Biology Lab (AICoB), Biotechnology Division, CSIR-Institute of Himalayan Bioresource Technology, Palampur, Himachal Pradesh, India.

Medicinal research reviews
|December 22, 2023
PubMed
概括

虚拟选 (VS),使用机器智能,通过有效选大型复合物库来加速药物发现. 这篇评论详细介绍了现代人工智能驱动的VS方法,以实现更快,更准确的打击识别.

关键词:
大数据就是大数据.遇到打击识别识别.击中优化优化的优化.综合虚拟选综合的虚拟选机器智能是一种机器智能.机器智能驱动的虚拟选虚拟选 虚拟选 虚拟选

更多相关视频

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
08:31

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

5.0K
Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.5K

相关实验视频

Last Updated: Jun 30, 2026

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.8K
Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
08:31

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

5.0K
Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.5K

科学领域:

  • 计算化学和化学信息学
  • 药物的发现和开发.
  • 医学中的人工智能

背景情况:

  • 虚拟查 (VS) 是现代药物发现的基石,传统上分为基于连接体 (LB) 和基于结构 (SB) 的方法.
  • 越来越多的化学和生物数据需要先进的计算方法来有效识别被击中分子.
  • 机器智能 (MI) 提供了强大的工具来提高VS的速度和准确性,减少时间和资源消耗.

研究的目的:

  • 审查和分类各种VS技术,强调机器智能的集成.
  • 详细介绍 VS 中机器学习和现代人工智能方法的实施情况.
  • 讨论当前VS方法的局限性,并探索未来的前景.

主要方法:

  • 关于传统LB和SB VS方法的文献综述.
  • 在VS中分析机器学习和AI算法应用.
  • 综合LB/SB技术和大数据驱动的VS策略的分类.

主要成果:

  • 由MI驱动的VS能够快速选超大库,大大缩短了匹配识别时间.
  • 综合LB/SB方法通过考虑连接体和标性质来提高预测准确性.
  • 先进的AI方法对于处理大数据和尽量减少药物发现中的错误阳性至关重要.

结论:

  • 机器智能正在彻底改变虚拟查,使其成为药物发现中更先进的技术.
  • VS的未来在于先进的智能解决方案,能够管理大数据并优化击中/领先的识别.
  • 对人工智能和计算架构的持续开发对于克服当前的局限性和提高VS有效性至关重要.