首页> 外文会议>Annual German Conference on Artificial Intelligence >Methods for Automated High-Throughput Toxicity Testing Using Zebrafish Embryos
【24h】

Methods for Automated High-Throughput Toxicity Testing Using Zebrafish Embryos

机译:使用斑马鱼胚胎自动化高通量毒性测试的方法

获取原文

摘要

In this paper, an automated process to extract experiment-specific parameters out of microscope images of zebrafish embryos is presented and applied to experiments consisting of toxicological treated zebrafish embryos. The treatments consist of a dilution series of several compounds. A custom built graphical user interface allows an easy labeling and browsing of the image data. Subsequently image-specific features are extracted for each image based on image processing algorithms. By means of feature selection, the most significant features are determined and a classification divides the images in two classes. Out of the classification results dose-response curves as well as frequently used general indicators of substance's acute toxicity can be automatically calculated. Exemplary the median lethal dose is determined. The presented approach was designed for real high-throughput screening including data handling and the results are stored in a long-time data storage and prepared to be processed on a cluster computing system being build up in the KIT. It provides the possibility to test any amount of chemical substances in high-throughput and is, in combination with new screening microscopes, able to manage ten thousands of risk tests required e.g. in the REACH framework or for drug discovery.
机译:本文介绍了一种从斑马鱼胚胎的显微镜图像中提取实验特异性参数的自动化方法,并应用于由毒理学处理的斑马鱼胚组成的实验。该处理包括几种化合物的稀释系列。自定义构建的图形用户界面允许轻松标记和浏览图像数据。随后基于图像处理算法针对每个图像提取特定图像特征。通过特征选择,确定最重要的特征,并且分类将图像划分为两个类。除了分类结果中,可以自动计算药物反应曲线以及物质的常用毒性的常用指标。确定中值致死剂量。所提出的方法是为真实的高吞吐量筛选而设计的,包括数据处理,结果存储在长期数据存储中,并准备好在套件中积聚的集群计算系统上处理。它提供了在高通量中测试任何数量的化学物质,并且与新的筛查显微镜相结合,能够管理需要10万风险测试。在REACH框架或药物发现中。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号