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相关概念视频

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
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
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
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 and Protein Structure02:15

Protein and Protein Structure

79.4K
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...
79.4K
Protein Organization01:24

Protein Organization

6.4K
Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....
6.4K

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相关实验视频

Updated: Jun 21, 2025

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

Published on: January 26, 2024

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深度学习方法用于蛋白质功能预测.

Frimpong Boadu1, Ahhyun Lee1, Jianlin Cheng1

  • 1Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, Missouri, USA.

Proteomics
|July 12, 2024
PubMed
概括
此摘要是机器生成的。

深度学习方法显著提升了蛋白质功能预测,这是生物信息学的一个关键挑战. 这篇评论强调了人工智能驱动的最新进展,挑战和计算生物学的未来方向.

关键词:
人工智能的人工智能是人工智能.深度学习是一种深度学习.基因本体学 基因本体学蛋白质功能的预测和预测.

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A Protocol for Computer-Based Protein Structure and Function Prediction
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A Protocol for Computer-Based Protein Structure and Function Prediction

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An Integrated Approach for Microprotein Identification and Sequence Analysis

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相关实验视频

Last Updated: Jun 21, 2025

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

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A Protocol for Computer-Based Protein Structure and Function Prediction
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A Protocol for Computer-Based Protein Structure and Function Prediction

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An Integrated Approach for Microprotein Identification and Sequence Analysis
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An Integrated Approach for Microprotein Identification and Sequence Analysis

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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
  • 人工智能的人工智能

背景情况:

  • 蛋白质功能预测对于生物研究和系统生物学至关重要.
  • 它仍然是生物信息学的一个重大挑战,需要先进的计算方法.
  • 传统的方法已经发展了二十多年,最近由于人工智能而加速.

研究的目的:

  • 提供对最近用于蛋白质功能预测的深度学习方法的深入审查.
  • 总结关键的进展,并确定该领域持续存在的挑战.
  • 建议未来的研究方向,并讨论相关数据源和指标.

主要方法:

  • 关于深度学习应用在蛋白质功能预测中的最新文献的综述.
  • 分析人工智能驱动的方法,包括序列,结构和交互数据.
  • 讨论在现场使用的常见数据集和评估指标.

主要成果:

  • 深度学习已经迅速提高了蛋白质功能预测的准确性和速度.
  • 通过利用人工智能 (AI) 取得了重大进展.
  • 一些重大挑战仍然存在,需要进一步的方法发展.

结论:

  • 深度学习为推进蛋白质功能预测提供了强大的工具.
  • 应对当前的挑战需要机器学习,人工智能和生物信息学专家之间的跨学科合作.
  • 进一步探索数据源和评估指标对于开发尖端方法至关重要.