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

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...
14.4K
Protein Organization01:24

Protein Organization

9.0K
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....
9.0K
Structural Protein Function01:56

Structural Protein Function

3.2K
3.2K
Structural Protein Function01:56

Structural Protein Function

29.7K
Structural proteins are a category of proteins responsible for functions ranging from cell shape and movement to providing support to major structures such as bones, cartilage, hair, and muscles. This group includes proteins such as collagen, actin, myosin, and keratin.
Collagen, the most abundant protein in mammals, is found throughout the body. In connective tissue, such as skin, ligaments, and tendons, it provides tensile strength and elasticity.  In bones and teeth, it mineralizes to...
29.7K
Protein Networks02:26

Protein Networks

4.4K
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,...
4.4K
Protein Networks02:26

Protein Networks

2.8K
2.8K

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

DeDoc2 Identifies and Characterizes the Hierarchy and Dynamics of Chromatin TAD-Like Domains in the Single Cells.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2023
Same author

DeTOKI identifies and characterizes the dynamics of chromatin TAD-like domains in a single cell.

Genome biology·2021
Same author

The PHU-NET: A robust phase unwrapping method for MRI based on deep learning.

Magnetic resonance in medicine·2021
Same author

<i>Phytophthora sojae</i> leucine-rich repeat receptor-like kinases: diverse and essential roles in development and pathogenicity.

iScience·2021
Same author

Thermodynamics Analysis and Removal of P in a P-(M)-H<sub>2</sub>O System.

Molecules (Basel, Switzerland)·2021
Same author

Nature-Inspired Structures Applied in Heat Transfer Enhancement and Drag Reduction.

Micromachines·2021

相关实验视频

Updated: Jan 8, 2026

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

69.6K

基于结构信息原则的积极机器人检测.

Xianghua Zeng, Hao Peng, Angsheng Li

    IEEE transactions on pattern analysis and machine intelligence
    |December 22, 2025
    PubMed
    概括
    此摘要是机器生成的。

    我们介绍SIAMD,这是一个用于社交机器人检测的新框架. 它使用结构信息和对抗性学习来模拟机器人的行为,以主动识别和对抗社交媒体上的复杂机器人.

    更多相关视频

    Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
    09:51

    Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

    Published on: July 16, 2017

    16.0K
    The Application of Open Searching-based Approaches for the Identification of Acinetobacter baumannii O-linked Glycopeptides
    08:37

    The Application of Open Searching-based Approaches for the Identification of Acinetobacter baumannii O-linked Glycopeptides

    Published on: November 2, 2021

    2.5K

    相关实验视频

    Last Updated: Jan 8, 2026

    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

    69.6K
    Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
    09:51

    Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

    Published on: July 16, 2017

    16.0K
    The Application of Open Searching-based Approaches for the Identification of Acinetobacter baumannii O-linked Glycopeptides
    08:37

    The Application of Open Searching-based Approaches for the Identification of Acinetobacter baumannii O-linked Glycopeptides

    Published on: November 2, 2021

    2.5K

    科学领域:

    • 计算机科学 计算机科学
    • 人工智能的人工智能
    • 社交网络分析 社交网络分析

    背景情况:

    • 机器人检测对于社交媒体真实性至关重要.
    • 复杂的机器人逃避目前的检测方法,创造军备竞赛.
    • 现有的方法与不断发展的机器人行为作斗争.

    研究的目的:

    • 提出一个新的框架,SIAMD,用于积极的社交机器人检测.
    • 用结构信息和对抗性学习有效地模拟机器人的行为.
    • 为了提高机器人检测的通用性,稳定性和可解释性.

    主要方法:

    • 将用户帐户和消息交互组织成一个异质结构.
    • 使用结构量化历史活动不确定性.
    • 利用大型语言模型进行合成内容生成和网络演变.

    主要成果:

    • SIAMD显著超过了最先进的机器人检测基线.
    • 在真实世界数据集上证明了有效性,可概括性和稳定性.
    • 通过对抗网络演变实现了增强的主动检测.

    结论:

    • SIAMD提供了一种强大而有效的社交机器人检测方法.
    • 该框架的对抗性质提高了它对抗复杂机器人的能力.
    • 结构信息原则和LLM集成提升机器人检测能力.