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Protein Families02:47

Protein Families

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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...
15.5K
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

18.9K
The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
18.9K
Tagging and Fusion Proteins01:24

Tagging and Fusion Proteins

6.8K
Proteins are involved in several cellular processes and biochemical reactions. Analyzing a specific protein of interest requires it to be isolated from the other proteins in the cell. This is achieved by overexpressing the specific gene in a suitable host to produce large quantities of the target protein. A tag or label is recombined with the gene to produce a fusion protein containing the target protein and the tag. The tags on these fusion proteins can then be used for easy detection and...
6.8K
Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

11.0K
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...
11.0K
Protein Networks02:26

Protein Networks

4.0K
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,...
4.0K
Mechanical Protein Function01:58

Mechanical Protein Function

2.1K
2.1K

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Updated: Jul 27, 2025

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

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

68.8K

TEMPROT:使用变压器嵌入和同质性搜索进行蛋白质功能注释.

Gabriel B Oliveira1, Helio Pedrini2, Zanoni Dias2

  • 1Institute of Computing, University of Campinas, Campinas, Brazil. gabriel.oliveira@ic.unicamp.br.

BMC bioinformatics
|June 8, 2023
PubMed
概括

我们开发了TEMPROT和TEMPROT+,使用序列模式和相似性进行蛋白质功能预测的计算方法. 这些模型实现了具有竞争力的结果,并克服了现有方法的长度限制.

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
  • 基因组学就是基因组学.

背景情况:

  • 高通量测序产生了大量的蛋白质数据,需要用于功能分析的计算方法.
  • 现有的基于序列的蛋白质分类方法存在局限性,特别是关于输入蛋白质长度.
  • 准确的蛋白质功能预测对于理解生物过程和疾病机制至关重要.

研究的目的:

  • 介绍TEMPROT,一种用于蛋白质功能预测的新型计算方法.
  • 介绍TEMPROT+,一个组合方法,将TEMPROT与BLASTp结合起来,以提高预测准确度.
  • 评估TEMPROT和TEMPROT+的性能与最先进的方法相比.

主要方法:

  • TEMPROT利用从预先训练的蛋白质序列架构中微调和嵌入提取.
  • TEMPROT+是TEMPROT和BLASTp的组合,这是一个局部序列对齐工具.
  • 在从CAFA3挑战数据库中获得的数据集上评估模型性能.

主要成果:

  • 在生物过程 (BP),细胞组件 (CC) 和分子功能 (MF) 实体学中,TEMPROT和TEMPROT+展示了竞争性表现.
  • 包括F-max,AuPRC和IAuPRC在内的关键指标显示出强的结果,F-max得分为0.581 (BP),0.692 (CC) 和0.662 (MF).
关键词:
自然语言处理自然语言处理.蛋白质功能的预测和预测变压器 变压器 变压器

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  • 与现有文献方法相比,提出的方法取得了最先进的结果.

    • 结论:

    • 通过有效分析氨基酸序列模式和同质性,TEMPROT和TEMPROT+提供竞争力的蛋白质功能预测.
    • 开发的模型克服了许多当前文献方法中普遍存在的蛋白质长度输入限制.
    • 这些进步有助于在生物信息学中更有效,更准确的蛋白质功能注释.