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

Mutagenicity and Carcinogenicity01:25

Mutagenicity and Carcinogenicity

1.4K
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...
1.4K

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

Cord-blood black carbon particle burden is associated with a C19MC small extracellular vesicle miRNA signature enriched for neurodevelopmental pathways.

Environmental research·2026
Same author

Transcriptomic responses to repeated exposure of human C3A liver spheroids to polystyrene nanoplastics.

Archives of toxicology·2026
Same author

Downregulation of <i>Trpv4</i> and <i>Klf2</i> in brain microvessels is associated with the progression of neurovascular dysfunction and cognitive impairment in a model of heart failure with preserved ejection fraction.

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism·2026
Same author

TabularQual: A spreadsheet-based format for annotating and curating logical models in SBML-qual.

bioRxiv : the preprint server for biology·2026
Same author

Cardiotoxicity adverse outcome pathway network: towards mechanistic and quantitative modelling.

Frontiers in toxicology·2026
Same author

Cord-blood black carbon burden is associated with coordinated inflammatory and heme-metabolic transcriptional programs at birth in Bradford, United Kingdom.

The Science of the total environment·2026

相关实验视频

Updated: Sep 14, 2025

Author Spotlight: Generating Neuronal Phenotypic Profiles - A Protocol to Culture and Image Human Midbrain Dopaminergic Neurons
09:21

Author Spotlight: Generating Neuronal Phenotypic Profiles - A Protocol to Culture and Image Human Midbrain Dopaminergic Neurons

Published on: July 7, 2023

1.7K

机器学习对使用毒基因组学概况的稳性化合物的分类.

Brian Bwanya1, Saad Lodhi1, Theo M de Kok1

  • 1Department of Translational Genomics, GROW Research Institute for Oncology and Developmental Biology, Maastricht University, Maastricht 6229 ER, the Netherlands.

Toxicology
|July 20, 2025
PubMed
概括
此摘要是机器生成的。

使用转录基因数据的机器学习模型可以预测药物诱导的肝硬化症. 支持矢量机 (SVM) 在人类和老鼠模型中表现出高精度,为化学风险评估提供了一个可扩展的工具.

关键词:
药物诱导的肝肥胖症 (DIHS)机器学习 (ML) 是指机器学习.稳态性预测的预测支持矢量机器 (SVM) 是一个支持矢量机器.

更多相关视频

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures
09:38

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures

Published on: January 7, 2019

8.7K
Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis
11:25

Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis

Published on: July 11, 2014

34.0K

相关实验视频

Last Updated: Sep 14, 2025

Author Spotlight: Generating Neuronal Phenotypic Profiles - A Protocol to Culture and Image Human Midbrain Dopaminergic Neurons
09:21

Author Spotlight: Generating Neuronal Phenotypic Profiles - A Protocol to Culture and Image Human Midbrain Dopaminergic Neurons

Published on: July 7, 2023

1.7K
Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures
09:38

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures

Published on: January 7, 2019

8.7K
Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis
11:25

Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis

Published on: July 11, 2014

34.0K

科学领域:

  • 毒理学 毒理学 毒理学
  • 计算生物学 计算生物学
  • 基因组学就是基因组学.

背景情况:

  • 新的方法方法正在推动毒性测试计算模型的开发.
  • 转录组数据越来越多地用于预测化学诱导的不良影响.
  • 药物诱导的肝肥胖症是化学安全评估中的一个重要问题.

研究的目的:

  • 将监督机器学习应用于转录组数据,以预测药物诱导的肝硬化症.
  • 在这个预测任务中评估不同机器学习分类器的性能.
  • 为了获得对药物诱导的肝肥胖症背后的生物过程的机制性见解.

主要方法:

  • 利用从原始人类肝细胞和大鼠肝脏模型 (体外和体内) 获得的基因表达数据的监督机器学习.
  • 评估了五个机器学习分类器,使用来自开放TG-GATE数据库的微阵列数据.
  • 对排名最高的预测基因进行了功能分析和丰富分析.

主要成果:

  • 支持矢量机 (SVM) 在所有模型中实现了最高的预测性能 (ROC-AUC:0.820人,0.975鼠在体外,0.966鼠在体内).
  • 丰富分析显示,预测基因与脂质代谢,线粒体功能,胰岛素信号和氧化应激有很强的关联.
  • 像CYP1A1,PLIN2和GCK这样的关键基因与脂质代谢和肝脏疾病有关,而其他基因则表明了新的转录基因信号.

结论:

  • 机器学习模型,特别是SVM,有效地使用转录组数据预测药物诱导的肝肥胖症.
  • 这些模型捕获生物相关的信号,并提供机械的洞察力,进入肥胖症的病原体.
  • SVM模型显示,它是一个可扩展和可解释的工具,用于化学风险评估和推进非动物试验方法.