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

Protein Organization01:13

Protein Organization

137.6K
Overview
137.6K
Protein Folding01:22

Protein Folding

118.0K
Overview
118.0K
Protein and Protein Structure02:15

Protein and Protein Structure

79.5K
Proteins are one of the most abundant organic molecules in living systems and have the most diverse range of functions of all macromolecules. Proteins may be structural, regulatory, contractile, or protective. They may serve in transport, storage, or membranes; or they may be toxins or enzymes. Their structures, like their functions, vary greatly. They are all, however, amino acid polymers arranged in a linear sequence.
A protein's shape is critical to its function. For example, an enzyme...
79.5K
Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

10.8K
Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to...
10.8K
Protein Families02:47

Protein Families

15.3K
Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key...
15.3K
Conserved Binding Sites01:49

Conserved Binding Sites

4.2K
Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
4.2K

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

Correlated clustering and projection for dimensionality reduction.

Machine learning: science and technology·2026
Same author

VARIANT: Web Server for Decoding and Analyzing Viral Mutations at Genome and Protein Levels.

ArXiv·2026
Same author

Manifold topological deep learning for biomedical data.

Nature communications·2026
Same author

A review of recent advances in generative artificial intelligence models for biomolecular sciences.

Acta pharmaceutica Sinica. B·2026
Same author

CAP: Commutative algebra prediction of protein-nucleic acid binding affinities.

Machine learning: science and technology·2026
Same author

Topology-preserving Hodge decomposition in the Eulerian representation.

Beijing journal of pure & applied mathematics·2026
Same journal

Algorithm-hardware co-design of neuromorphic networks with dual memory pathways.

Nature machine intelligence·2026
Same journal

Plagiarism in the Age of Generative Artificial Intelligence: The advent of generative artificial intelligence (GenAI) tools is challenging the scientific community's understanding of the meaning and significance of plagiarism. A new definition of research misconduct is needed that specifically addresses the use of GenAI writing tools.

Nature machine intelligence·2026
Same journal

Platonic representation of foundation machine learning interatomic potentials.

Nature machine intelligence·2026
Same journal

Immunotherapy drug target identification using machine learning and patient-derived tumour explant validation.

Nature machine intelligence·2026
Same journal

A generative artificial intelligence approach for peptide antibiotic optimization.

Nature machine intelligence·2026
Same journal

LLMs displaying less cognitive bias are not necessarily better decision makers.

Nature machine intelligence·2026
查看所有相关文章

相关实验视频

Updated: Jun 30, 2025

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

68.7K

超越AlphaFold的蛋白质结构预测

Guo-Wei Wei1,2,3

  • 1Department of Mathematics, Michigan State University, East Lansing, MI, USA.

Nature machine intelligence
|March 22, 2024
PubMed
概括
此摘要是机器生成的。

DeepFragLib利用深度神经网络来创建一个新的蛋白质片段库. 这一进步旨在提高计算生物学中蛋白质结构预测的准确性和效率.

更多相关视频

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

17.0K
RNA Secondary Structure Prediction Using High-throughput SHAPE
13:42

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

31.5K

相关实验视频

Last Updated: Jun 30, 2025

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

68.7K
Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

17.0K
RNA Secondary Structure Prediction Using High-throughput SHAPE
13:42

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

31.5K

科学领域:

  • 计算生物学是一种计算生物学.
  • 结构生物学是结构生物学.
  • 生物信息学是一种生物信息学.

背景情况:

  • 深度学习已在蛋白质结构预测方面展现出前途,以DeepMind的AlphaFold为例.
  • 准确的蛋白质结构预测对于理解生物功能和疾病机制至关重要.

研究的目的:

  • 为了介绍DeepFragLib,一个新的蛋白质特定碎片库.
  • 为了利用深层神经网络来改善蛋白质结构预测.

主要方法:

  • 使用深度神经网络开发一种特定蛋白质的片段库.
  • 集成深度学习技术用于碎片选择和组装.

主要成果:

  • DeepFragLib代表了在提升蛋白质结构预测方面的潜在下一步.
  • 该库旨在提高现有预测方法的准确性和效率.

结论:

  • DeepFragLib为结构生物学社区提供了一个新的资源.
  • 这种方法意味着在将深度学习应用于蛋白质结构建模方面的进展.