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

Toxic Reactions: Overview01:26

Toxic Reactions: Overview

921
When toxic substances penetrate the human body, they disseminate to various tissues, undergoing metabolic changes. This process yields reactive metabolites that may covalently bind with specific target molecules, resulting in toxicity.
Toxicity falls into two primary categories: local and systemic.
Local toxicity appears at the exposure site, such as protein denaturation caused by caustic substances.
In contrast, systemic toxicity requires the toxic agent's absorption and distribution,...
921
Mutagenicity and Carcinogenicity01:25

Mutagenicity and Carcinogenicity

1.2K
Mutagenicity and carcinogenicity refer to the ability of drugs to cause genetic defects and induce cancer, respectively. The International Agency for Research on Cancer (IARC) classifies agents into four groups based on their carcinogenic potential. Group 1 agents are known human carcinogens; group 2A agents are probably carcinogenic to humans; group 3 agents lack data to support their role in carcinogenesis; and group 4 includes agents for which data support that they are not likely to be...
1.2K
Types of Toxins01:36

Types of Toxins

1.6K
Humans continually engage with an environment rich in potentially harmful chemicals. These are introduced to our bodies through inhalation, ingestion, or skin contact. These chemicals exist in various forms, such as air and environmental pollutants, agricultural chemicals, organic solvents, and heavy metals.
Air pollutants, primarily gases, pose significant threats to respiratory health, leading to conditions like hypoxia, lung cancer, and in extreme cases, death.
Environmental pollutants like...
1.6K
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
Drug Discovery: Overview01:26

Drug Discovery: Overview

7.3K
Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
7.3K

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

[Research Progress of Immunotherapy for Brain Metastases in Patients 
with Drive Gene Negative NSCLC].

Zhongguo fei ai za zhi = Chinese journal of lung cancer·2018
Same author

Ratiometric fluorescent probes with a self-immolative spacer for real-time detection of β-galactosidase and imaging in living cells.

Analytica chimica acta·2018
Same author

Near-Infrared-Triggered in Situ Gelation System for Repeatedly Enhanced Photothermal Brachytherapy with a Single Dose.

ACS nano·2018
Same author

Visual tracking in high-dimensional particle filter.

PloS one·2018
Same author

LAMELLAR MACULAR HOLE WITH LAMELLAR HOLE-ASSOCIATED EPIRETINAL PROLIFERATION IN FAMILIAL EXUDATIVE VITREORETINOPATHY.

Retinal cases & brief reports·2018
Same author

Tailoring Chemotherapy for the African-Centric S47 Variant of TP53.

Cancer research·2018

相关实验视频

Updated: May 24, 2025

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans
09:01

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans

Published on: March 14, 2019

7.2K

一种小规模数据驱动和基于图形神经网络的化合物毒性预测方法.

Xin Zhao1, Shuyi Zhang1, Tao Zhang1

  • 1School of Electronic and Information Engineering, Tianjin University, 92 Weijin Road, Tianjin, 300072, Tianjin, China.

Computational biology and chemistry
|March 6, 2025
PubMed
概括

本研究引入了一个图形神经网络 (GNN) 模型,用于在药物发现中高效的小规模毒性预测. JLGCN-MTT模型提高了准确性,特别是在有限的数据的情况下,有助于识别更安全的化合物.

关键词:
图表神经网络的神经网络机器学习是机器学习.毒理学预测 毒理学预测转移学习转移学习

更多相关视频

A Neurite Outgrowth Assay and Neurotoxicity Assessment with Human Neural Progenitor Cell-Derived Neurons
07:41

A Neurite Outgrowth Assay and Neurotoxicity Assessment with Human Neural Progenitor Cell-Derived Neurons

Published on: August 6, 2020

7.4K
A Strategy to Identify Compounds that Affect Cell Growth and Survival in Cultured Mammalian Cells at Low-to-Moderate Throughput
00:12

A Strategy to Identify Compounds that Affect Cell Growth and Survival in Cultured Mammalian Cells at Low-to-Moderate Throughput

Published on: September 22, 2019

8.5K

相关实验视频

Last Updated: May 24, 2025

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans
09:01

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans

Published on: March 14, 2019

7.2K
A Neurite Outgrowth Assay and Neurotoxicity Assessment with Human Neural Progenitor Cell-Derived Neurons
07:41

A Neurite Outgrowth Assay and Neurotoxicity Assessment with Human Neural Progenitor Cell-Derived Neurons

Published on: August 6, 2020

7.4K
A Strategy to Identify Compounds that Affect Cell Growth and Survival in Cultured Mammalian Cells at Low-to-Moderate Throughput
00:12

A Strategy to Identify Compounds that Affect Cell Growth and Survival in Cultured Mammalian Cells at Low-to-Moderate Throughput

Published on: September 22, 2019

8.5K

科学领域:

  • 计算化学是一种计算化学.
  • 药物发现 药物发现
  • 毒理学 毒理学 毒理学

背景情况:

  • 毒性预测对于药物发现至关重要,但有限的数据构成了挑战.
  • 数据驱动模型为传统实验方法提供了有效的替代方案.
  • 图形神经网络 (GNN) 显示出化学性质预测的前景.

研究的目的:

  • 利用GNN开发一个小规模的,数据驱动的毒性预测方法.
  • 通过跨多种毒性类型的联合学习来提高预测准确性.
  • 为了利用转移学习,在有限的数据上进行可靠的预测.

主要方法:

  • 提出了多种毒性类型的联合学习策略.
  • 构建了一个基于图形的模型,命名为JLGCN-MTT.
  • 综合转移学习以利用各种毒性类型的数据.

主要成果:

  • 在12个毒性预测任务中,JLGCN-MTT的表现优于传统的机器学习和单任务GNN.
  • 在11个任务中,曲线下的面积 (AUC) 提高了10%以上.
  • 在小型训练数据集 (50-300个样本) 中观察到显著的AUC改善 (高达11%).

结论:

  • 拟议的JLGCN-MTT方法在小规模毒性预测方面实现了高精度.
  • 这种方法即使在特定毒性类型的数据稀缺的情况下也是有效的.
  • 这些发现支持使用数据驱动的GNN来有效和可靠地评估药物发现中的毒性.