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相关概念视频

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
Conservation of Protein Domains02:26

Conservation of Protein Domains

3.1K
3.1K
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 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
Molecular Chaperones and Protein Folding03:00

Molecular Chaperones and Protein Folding

17.9K
The native conformation of a protein is formed by interactions between the side chains of its constituent amino acids. When the amino acids cannot form these interactions, the protein cannot fold by itself and needs chaperones. Notably, chaperones do not relay any additional information required for the folding of polypeptides; the native conformation of a protein is determined solely by its amino acid sequence. Chaperones catalyze protein folding without being a part of the folded protein.
The...
17.9K

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相关实验视频

Updated: Jun 26, 2025

A Protocol for Computer-Based Protein Structure and Function Prediction
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热探测器:一个基于序列的热友蛋白质预测框架.

Han Yu1, Xiaozhou Luo1

  • 1Shenzhen Key Laboratory for the Intelligent Microbial Manufacturing of Medicines, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; University of Chinese Academy of Sciences, Beijing 100049, China; CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Center for Synthetic Biochemistry, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.

International journal of biological macromolecules
|May 18, 2024
PubMed
概括

一个新的计算框架ThermoFinder使用序列数据准确地预测热友蛋白质. 这种进步改进了现有的方法,为研究和工业提供了有价值的工具.

关键词:
机器学习是机器学习.序列分析是指进行序列分析.热友蛋白质预测的预测

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An Integrated Approach for Microprotein Identification and Sequence Analysis
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相关实验视频

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科学领域:

  • 生物化学 生物化学
  • 计算生物学 计算生物学
  • 生物信息学是一种生物信息学.

背景情况:

  • 热友蛋白对研究和工业至关重要.
  • 现有的识别热友蛋白的计算方法由于数据质量和模型效率存在局限性.
  • 需要改善热友蛋白质的预测模型.

研究的目的:

  • 开发一种新的,基于序列的计算框架,用于预测热友蛋白质.
  • 评估拟议框架的性能与现有最先进的工具相比.
  • 为了使基于回归的温度最佳值直接从蛋白质序列预测.

主要方法:

  • 开发一种新的基于序列的预测框架,名为ThermoFinder.
  • 使用基准和新建数据集进行模型培训和评估.
  • 采用特征除实验来确认方法的有效性.
  • 应用沙普利添加式解释 (SHAP) 进行特征重要性分析.

主要成果:

  • 在基准数据集上,ThermoFinder显著超过了以前的最先进的工具.
  • 特征除实验验证实了 ThermoFinder 方法的不同组件的贡献.
  • ThermoFinder在新建的数据集上展示了高性能和一致性,其中包括基于回归的温度最佳预测.
  • SHAP分析证实了ThermoFinder使用的功能的优点.

结论:

  • 热探测器 (ThermoFinder) 是一种高效和全面的框架,用于预测热友蛋白.
  • 该模型的开源可用性促进了其在学术研究和工业应用中的采用.
  • 这项工作通过提供高效和准确的预测工具来解决以前方法的局限性.