相关实验视频

Updated: Jul 7, 2026

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

机器学习框架用于预测细胞毒性和识别消毒副产品的毒性驱动因素

Rabbi Sikder1, Huichun Zhang2, Peng Gao3

  • 1Department of Civil and Environmental Engineering, South Dakota School of Mines and Technology, Rapid City, SD 57701, United States.

Journal of hazardous materials
|March 10, 2024
PubMed
概括

机器学习模型预测饮用水消毒副产品 (DBP) 细胞毒性. 原子,特别是和,显著影响毒性,提供一种更快的方法来评估污染物风险.

关键词:
适用性领域 适用性领域化学毒性预测化学毒性预测数据增强数据增强机器学习辅助的QSAR模型分子指纹是分子指纹.

更多相关视频

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox00:05

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox

Published on: August 28, 2019

13.9K
Author Spotlight: High-Throughput Toxicity Screening Using Zebrafish Embryo Startle Response Assay06:25

Author Spotlight: High-Throughput Toxicity Screening Using Zebrafish Embryo Startle Response Assay

Published on: January 12, 2024

1.4K

相关概念视频

Automated Microbial Diagnostics01:24

Automated Microbial Diagnostics

Automated diagnostic analyzers have transformed clinical microbiology by providing rapid and reliable methods for pathogen identification and antibiotic susceptibility testing. Among these systems, the Vitek 2 is widely used because it automates the traditionally labor-intensive processes of microbial identification (ID) and antibiotic susceptibility testing (AST), delivering standardized and timely results that are essential for effective patient care.Microbial Identification with ID CardsThe...