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-protein Interfaces02:04

Protein-protein Interfaces

13.3K
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...
13.3K
Protein Networks02:26

Protein Networks

4.1K
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,...
4.1K
Protein Families02:47

Protein Families

15.8K
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...
15.8K
Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

11.4K
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...
11.4K
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

4.9K
Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence...
4.9K
Conserved Binding Sites01:49

Conserved Binding Sites

4.4K
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...
4.4K

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

Graph Neural Network-Based Approaches for Protein Function Prediction.

Methods in molecular biology (Clifton, N.J.)·2025
Same author

A Survey of Pretrained Protein Language Models.

Methods in molecular biology (Clifton, N.J.)·2025
Same author

Large Context, Deeper Insights: Harnessing Large Language Models for Advancing Protein-Protein Interaction Analysis.

Methods in molecular biology (Clifton, N.J.)·2025
Same author

Large Language Model (LLM)-Based Advances in Prediction of Post-translational Modification Sites in Proteins.

Methods in molecular biology (Clifton, N.J.)·2025
Same author

CaLMPhosKAN: prediction of general phosphorylation sites in proteins via fusion of codon aware embeddings with amino acid aware embeddings and wavelet-based Kolmogorov-Arnold network.

Bioinformatics (Oxford, England)·2025
Same author

LMPTMSite: A Platform for PTM Site Prediction in Proteins Leveraging Transformer-Based Protein Language Models.

Methods in molecular biology (Clifton, N.J.)·2024
Same journal

Mapping the 3D Chromosome Organization of a Biosynthetic Gene Cluster by Capture Hi-C (CHi-C).

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Mapping the 3D Chromosome Organization of Streptomyces by Hi-C.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

CUT&Tag Epigenomic Profiling of Biosynthetic Gene Clusters in Arabidopsis thaliana.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Rhizobium rhizogenes-Mediated Hairy Root Transformation Protocol for Lotus japonicus and Other Legumes.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Characterization of Bioactive Saponins from Sea Cucumbers.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Methods for Functional Validation of Terpenoid Metabolic Clusters in Nicotiana benthamiana and Aspergillus oryzae.

Methods in molecular biology (Clifton, N.J.)·2026
查看所有相关文章

相关实验视频

Updated: Sep 13, 2025

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
06:50

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

2.0K

基于多任务学习的方法来预测蛋白质功能.

Soufia Bahmani1, Meenal Chaudhari2, Callen Carrier1

  • 1College of Computing, Michigan Technological University, Houghton, MI, USA.

Methods in molecular biology (Clifton, N.J.)
|July 29, 2025
PubMed
概括
此摘要是机器生成的。

多任务学习 (MTL) 通过利用跨相关任务的共享信息来改善蛋白质功能预测. 这种计算方法有助于弥合生物信息学中新发现的蛋白质的序列功能差距.

关键词:
它与DNA蛋白结合.深度学习是一种深度学习.基因本体学 (GO) 是一种基因本体学.金属结合地点 金属结合地点多任务学习 (MTL)后翻译修改 (PTM) 是指翻译后的修改.蛋白质功能的预测和预测蛋白质语言模型的模型蛋白蛋白相互作用 (PPI) 是一种与RNA蛋白结合的RNA蛋白结合

更多相关视频

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

68.9K
JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

3.3K

相关实验视频

Last Updated: Sep 13, 2025

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
06:50

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

2.0K
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

68.9K
JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

3.3K

科学领域:

  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学
  • 基因组学就是基因组学.

背景情况:

  • 通过先进的测序技术,蛋白质序列数据的快速增长已经超过了功能注释.
  • 在后基因组时代的一个重大挑战是了解新发现的蛋白质的作用.
  • "序列功能差距"需要有效的计算方法来预测蛋白质功能.

研究的目的:

  • 审查基于多任务学习 (MTL) 的方法来预测蛋白质功能.
  • 突出MTL在提高预测准确性和计算效率方面的潜力.
  • 为了应对大量未表征蛋白质的注释挑战.

主要方法:

  • 对用于蛋白质功能预测的多任务学习 (MTL) 方法的审查.
  • 探索MTL如何利用共享表示来整合相关预测任务中的信息.
  • 对提高生物信息学预测的计算策略的分析.

主要成果:

  • 多任务学习 (MTL) 在蛋白质功能预测中显示出更好的预测性能.
  • 在相关任务中整合共享功能是MTL成功的关键.
  • MTL提高了生物信息学工具的准确性和计算效率.

结论:

  • 多任务学习 (MTL) 是一种强大的计算策略,用于解决蛋白质序列功能差距.
  • 在大型生物数据库中,MTL为加速蛋白质的功能注释提供了一个有希望的途径.
  • 进一步开发和应用MTL方法对于后基因组生物学研究至关重要.