Classification and prediction of toxicity of chemicals using an automated phenotypic profiling of Caenorhabditis elegans
文献类型：期刊论文
| 作者 | Gao, Shan2,5; Zeng, Yingxin2; Jing, Haiming2; Zhang, Nan2; Li, Guojun2,5; Han, Jing-Dong J.3; Xian, Bo3; Chen, Weiyang4; Flavel, Matthew1; Jois, Markandeya1 |
| 刊名 | BMC PHARMACOLOGY & TOXICOLOGY
 |
| 出版日期 | 2018 |
| 卷号 | 19期号:-页码:18 |
| 关键词 | C. elegans Chemicals Toxicity Image analysis Phenotype |
| ISSN号 | 2050-6511 |
| DOI | 10.1186/s40360-018-0208-3 |
| 文献子类 | Article |
| 英文摘要 | Background: Traditional toxicological studies have relied heavily on various animal models to understand the effect of various compounds in a biological context. Considering the great cost, complexity and time involved in experiments using higher order organisms. Researchers have been exploring alternative models that avoid these disadvantages. One example of such a model is the nematode Caenorhabditis elegans. There are some advantages of C. elegans, such as small size, short life cycle, well defined genome, ease of maintenance and efficient reproduction. Methods: As these benefits allow large scale studies to be initiated with relative ease, the problem of how to efficiently capture, organize and analyze the resulting large volumes of data must be addressed. We have developed a new method for quantitative screening of chemicals using C. elegans. 33 features were identified for each chemical treatment. Results: The compounds with different toxicities were shown to alter the phenotypes of C. elegans in distinct and detectable patterns. We found that phenotypic profiling revealed conserved functions to classify and predict the toxicity of different chemicals. Conclusions: Our results demonstrate the power of phenotypic profiling in C. elegans under different chemical environments. |
| 学科主题 | Pharmacology & Pharmacy ; Toxicology |
| WOS关键词 | NEMATODE |
| 语种 | 英语 |
| WOS记录号 | WOS:000430414600002 |
| 出版者 | BIOMED CENTRAL LTD |
| 版本 | 出版稿 |
| 源URL | [http://202.127.25.144/handle/331004/1317]  |
| 专题 | 中国科学院上海生命科学研究院营养科学研究所 |
| 作者单位 | 1.La Trobe Univ, Sch Life Sci, Bundoora, Vic 3083, Australia; 2.Beijing Ctr Prevent Med Res, Beijing Ctr Dis Prevent & Control, Beijing Key Lab Diagnost & Traceabil Technol Food, Beijing 100013, Peoples R China; 3.Chinese Acad Sci, Collaborat Innovat Ctr Genet & Dev Biol, CAS Ctr Excellence Mol Cell Sci,Key Lab Computat, Max Planck Partner Inst Computat Biol,Shanghai In, 320 Yue Yang Rd, Shanghai 200031, Peoples R China; 4.Qilu Univ Technol, Shandong Acad Sci, Coll Informat, Jinan 250353, Shandong, Peoples R China; 5.Capital Med Univ, Sch Publ Hlth, Beijing Key Lab Environm Toxicol, Beijing 100069, Peoples R China, |
| 推荐引用方式 GB/T 7714 | Gao, Shan,Zeng, Yingxin,Jing, Haiming,et al. Classification and prediction of toxicity of chemicals using an automated phenotypic profiling of Caenorhabditis elegans[J]. BMC PHARMACOLOGY & TOXICOLOGY,2018,19(-):18. |
| APA | Gao, Shan.,Zeng, Yingxin.,Jing, Haiming.,Zhang, Nan.,Li, Guojun.,...&,.(2018).Classification and prediction of toxicity of chemicals using an automated phenotypic profiling of Caenorhabditis elegans.BMC PHARMACOLOGY & TOXICOLOGY,19(-),18. |
| MLA | Gao, Shan,et al."Classification and prediction of toxicity of chemicals using an automated phenotypic profiling of Caenorhabditis elegans".BMC PHARMACOLOGY & TOXICOLOGY 19.-(2018):18. |
入库方式： OAI收割
来源：上海营养与健康研究所
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