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 Networks02:26

Protein Networks

3.9K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
3.9K
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

15.2K
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...
15.2K
Protein-protein Interfaces02:04

Protein-protein Interfaces

12.5K
Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
12.5K
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
Protein and Protein Structure02:15

Protein and Protein Structure

78.5K
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...
78.5K

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

PSFF-PTM: A Coarse-Grained Force-Field Parameter Patch for Modeling Post-Translational Modification Effects on Biomolecular Condensates.

Journal of chemical theory and computation·2026
Same author

Constructing amorphous-crystalline FeS via coordination regulation of ethylenediamine for efficient Cr(VI) removal from groundwater.

Environmental research·2026
Same author

Estimated glucose disposal rate and cardiovascular risk in metabolically healthy adults: a nationwide prospective cohort study.

Scientific reports·2026
Same author

Double sulfuration promotes the activation of peroxydisulfate by Fe-based N/S co-doped biochar composites to degrade sulfapyridine: Synergistic effect and degradation mechanism.

Environmental research·2026
Same author

VISTA uncovers missing gene expression and spatial-induced information for spatial transcriptomic data analysis.

Communications biology·2026
Same author

Burden of stroke and its subtypes in young adults in Asia, 1990-2021: risk factors and future predictions.

Stroke and vascular neurology·2025

相关实验视频

Updated: Jun 5, 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

68.5K

学习一个通用的图形变压器,用于在不相似的序列中预测蛋白质功能.

Yiwei Fu1, Zhonghui Gu2, Xiao Luo3

  • 1School of Mathematical Sciences, Peking University, Beijing 100871, China.

GigaScience
|December 10, 2024
PubMed
概括
此摘要是机器生成的。

我们开发了GALA (Graph Adversarial Learning with Alignment),这是一种用于准确预测蛋白质功能的新型深度学习方法. 通过学习域不变表示,GALA增强了对新蛋白质的概括性,提高了生物洞察力.

关键词:
具有对抗性的学习.域名适应 域名适应图形变压器 图形变压器低序列的身份是相同的.蛋白质功能的预测和预测.

更多相关视频

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

7.2K
A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

1.6K

相关实验视频

Last Updated: Jun 5, 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

68.5K
Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

7.2K
A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

1.6K

科学领域:

  • 计算生物学 计算生物学
  • 生物信息学是一种生物信息学.
  • 机器学习 机器学习

背景情况:

  • 高通量测序产生了大量数据,超过了实验验证.
  • 深度学习为快速的蛋白质功能预测提供了有希望的解决方案.
  • 当前的深度学习模型可能会与远离训练数据的新型蛋白质作斗争.

研究的目的:

  • 引入图形对抗式学习与对齐 (GALA),一种用于蛋白质功能预测的通用深度学习方法.
  • 提高蛋白质功能预测模型对新型非同类蛋白质的概括性.
  • 为了提高蛋白质功能预测模型的解释性.

主要方法:

  • GALA集成了图形变压器架构和注意力聚合,用于统一的蛋白质序列和结构表示学习.
  • 具有域区分器的对抗性学习确保了域不变的蛋白质表示.
  • 标签嵌入生成并在隐藏空间中对齐以优化标签信息.

主要成果:

  • 在PDB和Swiss-Prot数据集上,GALA的性能与最先进的方法相美.
  • 该模型通过使用类激活映射识别关键功能残留物来证明生物可解释性.
  • 在未见的序列空间中预测蛋白质的功能时,GALA显示出极好的概括性.

结论:

  • GALA的对抗性学习和标签嵌入对齐产生域不变表示,提高了概括性.
  • 将AlphaFold2结构与GALA集成显示了对新发现的蛋白质序列进行注释的潜力.
  • GALA的实施是公开可用于研究的.