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Een High-throughput Assay voor de voorspelling van de chemische toxiciteit door geautomatiseerde fenotypische profilering van Caenorhabditis elegans
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A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans
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Een High-throughput Assay voor de voorspelling van de chemische toxiciteit door geautomatiseerde fenotypische profilering van Caenorhabditis elegans

7,065 Views

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09:01 min

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March 14, 2019

DOI:

10.3791/59082-v

DOI:
10.3791/59082-v

•

09:01 min
March 14, 2019

•

3 Views
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1Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning,Beijing Center for Disease Prevention and Control/Beijing Center of Preventive Medicine Research, China, 2College of Computer Science and Technology,Qilu University of Technology(Shandong Academy of Sciences), China, 3Key Laboratory of Computational Biology, CAS Center for Excellence in Molecular Cell Science, Collaborative Innovation Center for Genetics and Developmental Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences,Chinese Academy of Sciences, China, 4Beijing Key Laboratory of Environmental Toxicology, School of Public Health,Capital Medical University, China, 5School of Life Sciences,La Trobe University, Australia

Summary

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Een kwantitatieve methode is ontwikkeld om te identificeren en te voorspellen van de acute toxiciteit van chemische stoffen door het automatisch analyseren de fenotypische profilering van Caenorhabditis elegans. Dit protocol wordt beschreven hoe behandelen van wormen met chemicaliën in een 384-well-plate, vastleggen van video's en kwantificeren van toxicologische verwante fenotypen.

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Cite this Article

Gao, S., Chen, W., Zhang, N., Xu, C., Jing, H., Zhang, W., Han, G., Flavel, M., Jois, M., Zeng, Y., Han, J. J., Xian, B., Li, G. A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans. J. Vis. Exp. (145), e59082, doi:10.3791/59082 (2019).

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