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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
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-Protein Interfaces02:04

Protein-Protein Interfaces

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Ligand Binding Sites02:40

Ligand Binding Sites

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Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
12.7K
Protein Organization01:24

Protein Organization

6.3K
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....
6.3K
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...
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Updated: Jun 7, 2025

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay PCA in Living Cells
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从古典和基于机器学习的自然语言处理工具衍生出的蛋白质-蛋白质相互作用网络.

David J Degnan1, Clayton W Strauch2, Moses Y Obiri3

  • 1Biological Sciences Division, Pacific Northwest National Laboratory, 902 Battelle Blvd, Richland, Washington 99354, United States.

Journal of proteome research
|November 11, 2024
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概括

将蛋白质与蛋白质相互作用 (PPI) 的文本挖掘工具进行比较,可以发现权衡. 经典方法产生高的真正值但过度连接的网络,而机器学习和大型语言模型根据数据可用性提供不同的网络结构和性能.

关键词:
贝尔特 (BERT) 公司在 GPT 中,GPT 必须是 GPT.法学士 (LLM) 是一个专业.生物文本采矿 生物文本采矿大型语言模型.机器学习是机器学习.自然语言处理自然语言处理.关系提取关系提取

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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
  • 自然语言处理自然语言处理.

背景情况:

  • 蛋白与蛋白相互作用 (PPI) 对于理解生物机制至关重要,从免疫反应到像SARS-CoV-2这样的病毒感染.
  • 现有的PPI数据库对于新研究或研究不足的物种往往不完整.
  • 文本挖掘为构建PPI网络提供了有价值的替代方案.

研究的目的:

  • 为了比较经典文本处理,基于机器学习 (ML) 的NLP和基于大型语言模型 (LLM) 的NLP工具的性能,以提取PPI关系.
  • 评估通过不同的NLP方法生成的PPI网络的特征.

主要方法:

  • 评估的开源经典文本处理工具.
  • 评估基于ML的NLP方法用于关系提取.
  • 对比基于LLM的NLP工具用于PPI网络构建.
  • 分析网络属性,如真正率和网络结构.

主要成果:

  • 古典方法产生了高的真实阳性率,但导致了过度连接的网络.
  • 基于ML的NLP方法产生了较低的真实阳性率,但产生了与目标结构相似的网络.
  • 基于LLM的NLP方法显示出不同的性能,通常在经典和ML方法之间.
  • 模型性能受到提供的文本数据量的影响.

结论:

  • 对于PPI网络构建的NLP方法的选择取决于研究的具体需求和数据的可用性.
  • 当高灵敏度优先于网络特异性时,古典方法是合适的.
  • ML和LLM方法为更具结构代表性的网络提供了替代方案,性能根据数据量而异.