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相关概念视频

Protein Families02:47

Protein Families

16.6K
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...
16.6K
Protein Networks02:26

Protein Networks

4.5K
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,...
4.5K
Proteomics01:33

Proteomics

9.2K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
9.2K
Ribosome Profiling02:24

Ribosome Profiling

4.0K
Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
4.0K
Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

14.0K
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...
14.0K
Protein-protein Interfaces02:04

Protein-protein Interfaces

14.4K
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...
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相关实验视频

Updated: Jan 10, 2026

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes
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Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Published on: May 31, 2011

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MotifAE从蛋白质语言模型中揭示了功能序列模式:无监督发现和可解释性分析.

Chao Hou1, Di Liu2, Yufeng Shen1,2,3

  • 1Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032.

bioRxiv : the preprint server for biology
|November 24, 2025
PubMed
概括
此摘要是机器生成的。

一个新的框架MotifAE解码蛋白质语言模型 (pLMs),以揭示隐藏的序列模式. 这种可解释的方法增强了蛋白质功能发现和工程.

关键词:
健身景观 健身景观发现功能性动机的发现.模型的解释性可解释性蛋白质语言模型的模型

更多相关视频

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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Peptide-based Identification of Functional Motifs and their Binding Partners
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Peptide-based Identification of Functional Motifs and their Binding Partners

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相关实验视频

Last Updated: Jan 10, 2026

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes
07:55

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Published on: May 31, 2011

10.7K
A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

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Peptide-based Identification of Functional Motifs and their Binding Partners
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Peptide-based Identification of Functional Motifs and their Binding Partners

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科学领域:

  • 计算生物学是一种计算生物学.
  • 生物信息学是一种生物信息学.
  • 在蛋白质科学中的机器学习

背景情况:

  • 蛋白质语言模型 (pLMs) 捕捉进化序列模式,但其功能是黑子.
  • 解释学习模式对于理解蛋白质功能和工程至关重要.

研究的目的:

  • 开发一个不受监督的框架,MotifAE,用于解释pLMs学到的模式.
  • 为了能够发现和分析蛋白质序列内的功能动机和结构域.

主要方法:

  • 开发了MotifAE,这是一个使用稀疏自编码器 (SAE) 架构的无监督框架.
  • 加入了光滑性损失,以改善特征连贯性和图案识别.
  • 预计pLM嵌入到一个可解释的,稀疏的潜在空间.

主要成果:

  • MotifAE成功地识别了已知的功能动机和多样化的序列模式.
  • 该框架捕获了结构域,将特征激活与残留物重要性和域函数相关联.
  • 识别了与域折叠稳定性相关的特征,从而实现了更好的稳定性预测和工程.

结论:

  • MotifAE为系统的序列模式发现和解释提供了一个一般的框架.
  • 该方法推进了蛋白质功能分析,突变效应解释和理性蛋白质工程.
  • MotifAE促进了具有增强稳定性的蛋白质的工程.