{"title":"预测毒理学挑战2000-2001","authors":"C. Helma, R. King, Stefan Kramer, A. Srinivasan","doi":"10.1093/bioinformatics/17.1.107","DOIUrl":null,"url":null,"abstract":"We initiated the Predictive Toxicology Challenge (PTC) to stimulate the development of advanced SAR techniques for predictive toxicology models. The goal of this challenge is to predict the rodent carcinogenicity of new compounds based on the experimental results of the US National Toxicology Program (NTP). Submissions will be evaluated on quantitative and qualitative scales to select the most predictive models and those with the highest toxicological relevance. Availability: http://www.informatik.uni-freiburg.de/∼ml/ptc/ Contact: helma@informatik.uni-freiburg.de.","PeriodicalId":90576,"journal":{"name":"Journal of bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2001-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"221","resultStr":"{\"title\":\"The Predictive Toxicology Challenge 2000-2001\",\"authors\":\"C. Helma, R. King, Stefan Kramer, A. Srinivasan\",\"doi\":\"10.1093/bioinformatics/17.1.107\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We initiated the Predictive Toxicology Challenge (PTC) to stimulate the development of advanced SAR techniques for predictive toxicology models. The goal of this challenge is to predict the rodent carcinogenicity of new compounds based on the experimental results of the US National Toxicology Program (NTP). Submissions will be evaluated on quantitative and qualitative scales to select the most predictive models and those with the highest toxicological relevance. Availability: http://www.informatik.uni-freiburg.de/∼ml/ptc/ Contact: helma@informatik.uni-freiburg.de.\",\"PeriodicalId\":90576,\"journal\":{\"name\":\"Journal of bioinformatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"221\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of bioinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/bioinformatics/17.1.107\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/bioinformatics/17.1.107","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We initiated the Predictive Toxicology Challenge (PTC) to stimulate the development of advanced SAR techniques for predictive toxicology models. The goal of this challenge is to predict the rodent carcinogenicity of new compounds based on the experimental results of the US National Toxicology Program (NTP). Submissions will be evaluated on quantitative and qualitative scales to select the most predictive models and those with the highest toxicological relevance. Availability: http://www.informatik.uni-freiburg.de/∼ml/ptc/ Contact: helma@informatik.uni-freiburg.de.
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