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相关概念视频

Protein Organization01:13

Protein Organization

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Overview
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Protein Organization01:24

Protein Organization

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

Conservation of Protein Domains Over Different Proteins

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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...
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Conservation of Protein Domains

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Proteins: From Genes to Degradation02:11

Proteins: From Genes to Degradation

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Within a biological system, the DNA encodes the RNA, and the nucleotide sequence in the RNA further defines the amino acid sequence in the protein. This is referred to as “The Central Dogma of Molecular Biology” - a term coined by Francis Crick.  Central dogma is a firm principle in biology that defines the flow of genetic information within any life form. The two fundamental steps in central dogma are - transcription and translation.
Transcription is the synthesis of RNA...
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民主化蛋白质语言模型培训,共享和协作

Jin Su1,2, Zhikai Li2, Tianli Tao2

  • 1Zhejiang University, Hangzhou, China.

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概括

研究人员现在可以在没有深度机器学习专业知识的情况下使用新的SaprotHub平台来训练和部署蛋白质语言模型. 这一框架使各种蛋白质应用的协作模型构建和共享成为可能.

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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:

  • 训练大规模的蛋白质语言模型需要专门的机器学习专业知识,这限制了许多研究人员的可访问性.
  • 现有的平台可能缺乏用于模型训练,预测和管理的直观接口.

研究的目的:

  • 推出SaprotHub,这是一个可访问的平台,用于培训和部署蛋白质语言模型.
  • 让没有深度机器学习背景的研究人员能够利用并为蛋白质模型开发做出贡献.
  • 为了促进定制蛋白质模型的协作构建,存储和共享.

主要方法:

  • 开发了SaprotHub平台,具有直观的用户界面.
  • 与谷歌 Colab 集成,以创建 ColabSaprot 框架.
  • 启用模型训练,预测,存储和共享的功能.

主要成果:

  • SaprotHub降低了蛋白质语言模型开发的进入障碍.
  • 科拉布萨普罗特框架支持各种与蛋白质相关的培训和预测任务.
  • 促进合作模式的创建和研究人员之间的传播.

结论:

  • SaprotHub使访问先进的蛋白质语言建模工具变得民主化.
  • 该平台促进了合作,并加速了蛋白质科学的研究.
  • 能够为特定的研究需求开发定制模型.