JoVE Journal
Environment
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꼬마 선 충 의 프로 파일링 Phenotypic 자동화 하 여 화학 독성의 예측에 대 한 높은 처리량 분석 결과
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Article
DOI:
10.3791/59082-v
•
09:01 min
•
March 14th, 2019
꼬마 선 충 의 프로 파일링 Phenotypic 자동화 하 여 화학 독성의 예측에 대 한 높은 처리량 분석 결과
March 14th, 2019
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Shan Gao*1, Weiyang Chen*2, Nan Zhang1, Chi Xu3, Haiming Jing1,4, Wenjing Zhang1,4, Gaochao Han1,4, Matthew Flavel5, Markandeya Jois5, Yingxin Zeng1, Jing-Dong J. Han3, Bo Xian3, Guojun Li1,4
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
* These authors contributed equally
Chapters
Summary
Please note that all translations are automatically generated.
Click here for the English version.
양적 방법 확인 하 고 자동으로 꼬마 선 충의 phenotypic 프로 파일링 분석 하 여 화학 물질의 급성 독성 예측 개발 되었습니다. 이 프로토콜 384-잘 접시에 화학 물질과 웜 치료, 비디오, 캡처 및 독물학 관련된 고기를 계량 하는 방법을 설명 합니다.