Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

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

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Sertoli cells-derived exosomal miR-30a-5p regulates ubiquitin E3 ligase Zeb2 to affect the spermatogonial stem cells proliferation and differentiation.

Reproductive toxicology (Elmsford, N.Y.)·2023
Same author

Polymorphisms in TRIB2 and CAPRIN2 Genes Contribute to the Susceptibility to High Myopia-Induced Cataract in Han Chinese Population.

Medical science monitor : international medical journal of experimental and clinical research·2023
Same author

CoP@Ni core-shell heterostructure nanowire array: A highly efficient electrocatalyst for hydrogen evolution.

Journal of colloid and interface science·2023
Same author

Duck gasdermin E is a substrate of caspase-3/-7 and an executioner of pyroptosis.

Frontiers in immunology·2023
Same author

Vitamin B12 Ameliorates the Pathological Phenotypes of Multiple Parkinson's Disease Models by Alleviating Oxidative Stress.

Antioxidants (Basel, Switzerland)·2023
Same author

Encapsulating a Ni(II) molecular catalyst in photoactive metal-organic framework for highly efficient photoreduction of CO<sub>2</sub>.

Science bulletin·2023

相关实验视频

Updated: Jun 19, 2025

Immunopeptidomics: Isolation of Mouse and Human MHC Class I- and II-Associated Peptides for Mass Spectrometry Analysis
09:32

Immunopeptidomics: Isolation of Mouse and Human MHC Class I- and II-Associated Peptides for Mass Spectrometry Analysis

Published on: October 15, 2021

11.8K

GIHP:基于图形卷积神经网络的可解释泛特定HLA结合亲和度预测.

Lingtao Su1, Yan Yan2, Bo Ma3

  • 1Shandong University of Science and Technology, Qingdao, China.

Frontiers in genetics
|July 25, 2024
PubMed
概括

这项研究引入了GIHP,一种可解释的图形卷积神经网络,以准确预测人类白细胞抗原 (HLA) - 结合亲缘关系. 该方法通过识别癌症数据集中预测患者存活率的关键残留物来增强免疫疗法.

关键词:
美国GCNN它与HLA结合.亲缘关系预测的预测.免疫疗法 免疫疗法模型解释解释模型解释

更多相关视频

A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes
07:59

A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes

Published on: March 25, 2014

14.9K
Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
06:50

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

1.8K

相关实验视频

Last Updated: Jun 19, 2025

Immunopeptidomics: Isolation of Mouse and Human MHC Class I- and II-Associated Peptides for Mass Spectrometry Analysis
09:32

Immunopeptidomics: Isolation of Mouse and Human MHC Class I- and II-Associated Peptides for Mass Spectrometry Analysis

Published on: October 15, 2021

11.8K
A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes
07:59

A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes

Published on: March 25, 2014

14.9K
Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
06:50

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

1.8K

科学领域:

  • 免疫信息学是指免疫信息学.
  • 计算生物学 计算生物学
  • 结构生物学 结构生物学

背景情况:

  • 准确预测人类白细胞抗原 (HLA) - 结合亲缘关系对于疫苗开发和免疫疗法设计至关重要.
  • 目前的基于序列的方法缺乏结构洞察力和模型解释性,阻碍了关键结合残留物的识别.
  • 了解HLA-相互作用对于破译自适应性免疫反应至关重要.

研究的目的:

  • 开发一种可解释的预测方法,用于包含结构信息的HLA-结合亲缘关系.
  • 为了提高模型的解释性,以识别参与HLA-结合的关键氨基酸.
  • 验证已识别的关键残留物在预测免疫治疗结果中的临床相关性.

主要方法:

  • 拟议的GIHP,一个可解释的图形卷积神经网络 (GCNN) 模型.
  • 代表了HLA结构作为氨基酸水平图和SMILE字符串作为原子水平图.
  • 开发了一种新的视觉解释方法,即渐变加权激活映射 (Grad-WAM),用于识别关键结合残留物.

主要成果:

  • 与多个数据集的最先进方法相比,GIHP显示出更高的预测准确性.
  • 确定了关键的HLA-结合残留物,并验证了它们在区分免疫治疗患者存活率组中的能力.
  • 鉴定的残留物成功地将患者的生存率分为乳腺,膀和泛癌数据集.

结论:

  • GIHP显著提高了HLA-结合预测的准确性和可解释性.
  • 已识别的关键残留物有可能指导个性化癌症免疫治疗策略.
  • 这项工作为利用免疫信息学中的结构和可解释模型提供了基础.