SwePub
Sök i LIBRIS databas

  Utökad sökning

WFRF:(Sine W)
 

Sökning: WFRF:(Sine W) > CERAPP :

LIBRIS Formathandbok  (Information om MARC21)
FältnamnIndikatorerMetadata
00009736naa a2200817 4500
001oai:DiVA.org:umu-120258
003SwePub
008160512s2016 | |||||||||||000 ||eng|
0247 a https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1202582 URI
0247 a https://doi.org/10.1289/ehp.15102672 DOI
040 a (SwePub)umu
041 a engb eng
042 9 SwePub
072 7a ref2 swepub-contenttype
072 7a art2 swepub-publicationtype
1001 a Mansouri, Kamelu National Center for Computational Toxicology, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA4 aut
2451 0a CERAPP :b Collaborative Estrogen Receptor Activity Prediction Project
264 1b Environmental Health Perspectives,c 2016
338 a electronic2 rdacarrier
520 a BACKGROUND: Humans are exposed to thousands of man-made chemicals in the environment. Some chemicals mimic natural endocrine hormones and, thus, have the potential to be endocrine disruptors. Most of these chemicals have never been tested for their ability to interact with the estrogen receptor (ER). Risk assessors need tools to prioritize chemicals for evaluation in costly in vivo tests, for instance, within the U.S. EPA Endocrine Disruptor Screening Program. OBJECTIVES: We describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) and demonstrate the efficacy of using predictive computational models trained on high-throughput screening data to evaluate thousands of chemicals for ER-related activity and prioritize them for further testing. METHODS: CERAPP combined multiple models developed in collaboration with 17 groups in the United States and Europe to predict ER activity of a common set of 32,464 chemical structures. Quantitative structure-activity relationship models and docking approaches were employed, mostly using a common training set of 1,677 chemical structures provided by the U.S. EPA, to build a total of 40 categorical and 8 continuous models for binding, agonist, and antagonist ER activity. All predictions were evaluated on a set of 7,522 chemicals curated from the literature. To overcome the limitations of single models, a consensus was built by weighting models on scores based on their evaluated accuracies. RESULTS: Individual model scores ranged from 0.69 to 0.85, showing high prediction reliabilities. Out of the 32,464 chemicals, the consensus model predicted 4,001 chemicals (12.3%) as high priority actives and 6,742 potential actives (20.8%) to be considered for further testing.CONCLUSION: This project demonstrated the possibility to screen large libraries of chemicals using a consensus of different in silico approaches. This concept will be applied in future projects related to other end points.
650 7a NATURVETENSKAPx Kemi0 (SwePub)1042 hsv//swe
650 7a NATURAL SCIENCESx Chemical Sciences0 (SwePub)1042 hsv//eng
650 7a NATURVETENSKAPx Data- och informationsvetenskapx Datavetenskap0 (SwePub)102012 hsv//swe
650 7a NATURAL SCIENCESx Computer and Information Sciencesx Computer Sciences0 (SwePub)102012 hsv//eng
7001 a Abdelaziz, Ahmedu Institute of Structural Biology, Helmholtz Zentrum Muenchen – German Research Center for Environmental Health (GmbH), Munich, Germany4 aut
7001 a Rybacka, Aleksandrau Umeå universitet,Kemiska institutionen4 aut0 (Swepub:umu)alry0007
7001 a Roncaglioni, Alessandrau Environmental Chemistry and Toxicology Laboratory, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy4 aut
7001 a Tropsha, Alexanderu Laboratory for Molecular Modeling, University of North Carolina, Chapel Hill, North Carolina, USA4 aut
7001 a Varnek, Alexandreu Laboratoire de Chemoinformatique, University of Strasbourg, Strasbourg, France4 aut
7001 a Zakharov, Alexeyu National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA4 aut
7001 a Worth, Andrewu Institute for Health and Consumer Protection (IHCP), Joint Research Centre of the European Commission in Ispra, Ispra, Italy4 aut
7001 a Richard, Ann M.u National Center for Computational Toxicology, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA4 aut
7001 a Grulke, Christopher M.u National Center for Computational Toxicology, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA4 aut
7001 a Trisciuzzi, Danielau Department of Pharmacy-Drug Sciences, University of Bari, Bari, Italy4 aut
7001 a Fourches, Denisu Laboratory for Molecular Modeling, University of North Carolina, Chapel Hill, North Carolina, USA4 aut
7001 a Horvath, Dragosu Laboratoire de Chemoinformatique, University of Strasbourg, Strasbourg, France4 aut
7001 a Benfenati, Emiliou Environmental Chemistry and Toxicology Laboratory, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy4 aut
7001 a Muratov, Eugeneu Laboratory for Molecular Modeling, University of North Carolina, Chapel Hill, North Carolina, USA4 aut
7001 a Wedebye, Eva Bayu National Food Institute, Division of Toxicology and Risk Assessment, Technical University of Denmark, Copenhagen, Denmark4 aut
7001 a Grisoni, Francescau Milano Chemometrics and QSAR Research Group, University of Milano-Bicocca, Milan, Italy4 aut
7001 a Mangiatordi, Giuseppe F.u Department of Pharmacy-Drug Sciences, University of Bari, Bari, Italy4 aut
7001 a Incisivo, Giuseppina M.u Environmental Chemistry and Toxicology Laboratory, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy4 aut
7001 a Hong, Huixiaou National Center for Toxicological Research, Division of Bioinformatics and Biostatistics, U.S. Food and Drug Administration, Jefferson, Arizona, USA4 aut
7001 a Ng, Hui W.u National Center for Toxicological Research, Division of Bioinformatics and Biostatistics, U.S. Food and Drug Administration, Jefferson, Arizona, USA4 aut
7001 a Tetko, Igor V.u Institute of Structural Biology, Helmholtz Zentrum Muenchen – German Research Center for Environmental Health (GmbH), Munich, Germany4 aut
7001 a Balabin, Ilyau High Performance Computing, Lockheed Martin, Research Triangle Park, North Carolina, USA4 aut
7001 a Kancherla, Jayaramu National Center for Computational Toxicology, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA4 aut
7001 a Shen, Jieu Research Institute for Fragrance Materials, Inc., Woodcliff Lake, New Jersey, USA4 aut
7001 a Burton, Julienu Institute for Health and Consumer Protection (IHCP), Joint Research Centre of the European Commission in Ispra, Ispra, Italy4 aut
7001 a Nicklaus, Marcu National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA4 aut
7001 a Cassotti, Matteou Milano Chemometrics and QSAR Research Group, University of Milano-Bicocca, Milan, Italy4 aut
7001 a Nikolov, Nikolai G.u National Food Institute, Division of Toxicology and Risk Assessment, Technical University of Denmark, Copenhagen, Denmark4 aut
7001 a Nicolotti, Oraziou Department of Pharmacy-Drug Sciences, University of Bari, Bari, Italy4 aut
7001 a Andersson, Patrik L.u Umeå universitet,Kemiska institutionen4 aut0 (Swepub:umu)paan0001
7001 a Zang, Qingdau Integrated Laboratory Systems, Inc., Research Triangle Park, North Carolina, USA4 aut
7001 a Politi, Reginau Laboratory for Molecular Modeling, University of North Carolina, Chapel Hill, North Carolina, USA4 aut
7001 a Beger, Richard D.u National Center for Toxicological Research, Division of Systems Biology, U.S. Food and Drug Administration, Jefferson, Arizona, USA4 aut
7001 a Todeschini, Robertou Milano Chemometrics and QSAR Research Group, University of Milano-Bicocca, Milan, Italy4 aut
7001 a Huang, Ruiliu National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland, USA4 aut
7001 a Farag, Sherifu Laboratory for Molecular Modeling, University of North Carolina, Chapel Hill, North Carolina, USA4 aut
7001 a Rosenberg, Sine A.u National Food Institute, Division of Toxicology and Risk Assessment, Technical University of Denmark, Copenhagen, Denmark4 aut
7001 a Slavov, Svetoslavu National Center for Toxicological Research, Division of Systems Biology, U.S. Food and Drug Administration, Jefferson, Arizona, USA4 aut
7001 a Hu, Xinu National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland, USA4 aut
7001 a Judson, Richard S.u National Center for Computational Toxicology, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA4 aut
7102 a National Center for Computational Toxicology, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USAb Institute of Structural Biology, Helmholtz Zentrum Muenchen – German Research Center for Environmental Health (GmbH), Munich, Germany4 org
7730 t Journal of Environmental Health Perspectivesd : Environmental Health Perspectivesg 124:7, s. 1023-1033q 124:7<1023-1033x 0091-6765x 1552-9924
8564 u https://doi.org/10.1289/ehp.1510267y Fulltext
8564 u https://umu.diva-portal.org/smash/get/diva2:927646/FULLTEXT02.pdfx primaryx Raw objecty fulltext:print
8564 u https://ehp.niehs.nih.gov/doi/pdf/10.1289/ehp.1510267
8564 8u https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-120258
8564 8u https://doi.org/10.1289/ehp.1510267

Hitta via bibliotek

Till lärosätets databas

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy