数据库名称：InterPred
数据库简述：
所属国家/地区：United States
数据库主要信息：InterPred is a platform to predict such interference chemicals based on the first large-scale chemical screening effort to directly characterize chemical-assay interference, using assays in the Tox21 portfolio specifically designed to measure autofluorescence and luciferase inhibition. InterPred combines 17 quantitative structure activity relationship (QSAR) models built using optimized machine learning techniques and allows users to predict the probability that a new chemical will interfere with different combinations of cellular and technology conditions. InterPred models have been applied to the entire Distributed Structure-Searchable Toxicity (DSSTox) Database (∼800,000 chemicals).
建立年份：2020
联系信息：Contact information
University/Institution:
National Institute of Environmental Health Sciences
Address:
RTP, NC 27709, USA
City:
Province/State:
North Carolina
Country/Region:
United States
Contact name (PI/Team):
Nicole C Kleinstreuer
Contact email (PI/Helpdesk):
nicole.kleinstreuer@nih.gov
