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相关概念视频

Protein Networks02:26

Protein Networks

3.9K
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,...
3.9K
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...
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相关实验视频

Updated: Jun 21, 2025

Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing
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Cmai:从大规模测序数据中预测抗原-抗体相互作用

Bing Song, Kaiwen Wang, Saiyang Na

    bioRxiv : the preprint server for biology
    |July 15, 2024
    PubMed
    概括
    此摘要是机器生成的。

    我们开发了Cmai,这是一种用于高通量抗体-抗原结合预测的AI工具. 该工具有助于识别免疫检查点抑制剂 (ICI) 治疗反应的生物标志物,并了解与免疫相关的不良事件 (irAEs).

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    Interactome-Seq: A Protocol for Domainome Library Construction, Validation and Selection by Phage Display and Next Generation Sequencing
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    Interactome-Seq: A Protocol for Domainome Library Construction, Validation and Selection by Phage Display and Next Generation Sequencing

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    相关实验视频

    Last Updated: Jun 21, 2025

    Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing
    08:51

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    Published on: March 15, 2019

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    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

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    Interactome-Seq: A Protocol for Domainome Library Construction, Validation and Selection by Phage Display and Next Generation Sequencing
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    科学领域:

    • 免疫学 免疫学 免疫学
    • 生物信息学是一种生物信息学.
    • 人工智能的人工智能

    背景情况:

    • 抗体-抗原相互作用对于幽默免疫非常重要.
    • 目前用于分析这些相互作用的方法受到成本,时间和吞吐量的限制.
    • 现有的生物信息学工具专注于抗体优化,而不是绑定预测.

    研究的目的:

    • 开发一种可扩展,高通量的人工智能工具,用于预测抗体-抗原结合.
    • 使用人工智能预测的绑定数据创建生物标记指标,用于翻译应用.
    • 为了研究与免疫相关的不良事件 (irAEs) 和癌症免疫治疗中的幽默性免疫反应.

    主要方法:

    • 开发一种名为Cmai的人工智能工具,用于抗体-抗原结合预测.
    • 将Cmai应用于高通量B细胞受体 (BCR) 测序数据.
    • 根据Cmai的输出设计了一个生物标记指标,用于分析免疫反应.

    主要成果:

    • 在验证过程中,Cmai 获得了 0.91 的 AUROC.
    • 在irAEs期间,幽默免疫优先准细胞内抗原.
    • 细胞外瘤抗原驱动B细胞透和与瘤细胞的同定位.
    • 丰富的瘤抗原向抗体预测了对免疫检查点抑制剂 (ICI) 治疗的反应.

    结论:

    • Cmai为高通量抗体-抗原结合预测提供了一个可扩展的解决方案.
    • 开发的生物标志物方法为IRE和ICI治疗疗效提供了洞察力.
    • 这项工作解决了当前抗体信息学和蛋白质复合体预测工具的局限性.