LEADER 03215nam 2200421z- 450 001 9910227348503321 005 20210212 035 $a(CKB)4100000000883848 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/61064 035 $a(oapen)doab61064 035 $a(EXLCZ)994100000000883848 100 $a20202102d2017 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aTox21 Challenge to Build Predictive Models of Nuclear Receptor and Stress Response Pathways as Mediated by Exposure to Environmental Toxicants and Drugs 210 $cFrontiers Media SA$d2017 215 $a1 online resource (102 p.) 225 1 $aFrontiers Research Topics 311 08$a2-88945-197-6 330 $aTens of thousands of chemicals are released into the environment every day. High-throughput screening (HTS) has offered a more efficient and cost-effective alternative to traditional toxicity tests that can profile these chemicals for potential adverse effects with the aim to prioritize a manageable number for more in depth testing and to provide clues to mechanism of toxicity. The Tox21 program, a collaboration between the National Institute of Environmental Health Sciences (NIEHS)/National Toxicology Program (NTP), the U.S. Environmental Protection Agency's (EPA) National Center for Computational Toxicology (NCCT), the National Institutes of Health (NIH) National Center for Advancing Translational Sciences (NCATS), and the U.S. Food and Drug Administration (FDA), has generated quantitative high-throughput screening (qHTS) data on a library of 10K compounds, including environmental chemicals and drugs, against a panel of nuclear receptor and stress response pathway assays during its production phase (phase II). The Tox21 Challenge, a worldwide modeling competition, was launched that asks a "crowd" of researchers to use these data to elucidate the extent to which the interference of biochemical and cellular pathways by compounds can be inferred from chemical structure data. In the Challenge participants were asked to model twelve assays related to nuclear receptor and stress response pathways using the data generated against the Tox21 10K compound library as the training set. The computational models built within this Challenge are expected to improve the community's ability to prioritize novel chemicals with respect to potential concern to human health. This research topic presents the resulting computational models with good predictive performance from this Challenge. 606 $aEnvironmental economics$2bicssc 610 $aHTS 610 $ain vitro assay 610 $anuclear receptor 610 $apredictive model 610 $aQSAR 610 $astress response 610 $aTox21 615 7$aEnvironmental economics 700 $aXia$b Menghang$4auth$01838548 702 $aRuili Huang$4auth 906 $aBOOK 912 $a9910227348503321 996 $aTox21 Challenge to Build Predictive Models of Nuclear Receptor and Stress Response Pathways as Mediated by Exposure to Environmental Toxicants and Drugs$94417534 997 $aUNINA