Use of in vitro HTS-derived concentration-response data as biological descriptors improves the accuracy of QSAR models of in vivo toxicity.
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Big data in chemical toxicity research: the use of high-throughput screening assays to identify potential toxicantsA Survey of Quantitative Descriptions of Molecular StructureProfiling animal toxicants by automatically mining public bioassay data: a big data approach for computational toxicologyQSAR modeling: where have you been? Where are you going to?Building a robust 21st century chemical testing program at the U.S. Environmental Protection Agency: recommendations for strengthening scientific engagementMechanism Profiling of Hepatotoxicity Caused by Oxidative Stress Using Antioxidant Response Element Reporter Gene Assay Models and Big DataPredictive modeling of chemical hazard by integrating numerical descriptors of chemical structures and short-term toxicity assay dataPredictive Modeling of Estrogen Receptor Binding Agents Using Advanced Cheminformatics Tools and Massive Public DataParadigm shift in toxicity testing and modeling.Developing Enhanced Blood-Brain Barrier Permeability Models: Integrating External Bio-Assay Data in QSAR ModelingA Data Analysis Pipeline Accounting for Artifacts in Tox21 Quantitative High-Throughput Screening AssaysPredicting drug-induced hepatotoxicity using QSAR and toxicogenomics approaches.CurveP Method for Rendering High-Throughput Screening Dose-Response Data into Digital Fingerprints.Real-time cell toxicity profiling of Tox21 10K compounds reveals cytotoxicity dependent toxicity pathway linkage.Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches.Design, synthesis and experimental validation of novel potential chemopreventive agents using random forest and support vector machine binary classifiers.The use of pseudo-equilibrium constant affords improved QSAR models of human plasma protein bindingMedicinal chemistry for 2020Cell-Based High-Throughput Screening for Aromatase Inhibitors in the Tox21 10K LibraryQuantitative high-throughput screening for chemical toxicity in a population-based in vitro modelCHEMICAL AND BIOLOGICAL DESCRIPTOR INTEGRATION IMPROVES COMPUTATIONAL MODELING OF IN VIVO RAT TOXICITY.Getting the most out of PubChem for virtual screeningIn vitro screening for population variability in toxicity of pesticide-containing mixturesPrediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure-based modeling methodsTHE INTERACTIVE DECISION COMMITTEE FOR CHEMICAL TOXICITY ANALYSIS.From QSAR to QSIIR: searching for enhanced computational toxicology models.Integrative approaches for predicting in vivo effects of chemicals from their structural descriptors and the results of short-term biological assays.In Silico Models for Acute Systemic Toxicity.Hybrid in silico models for drug-induced liver injury using chemical descriptors and in vitro cell-imaging information.Accounting Artifacts in High-Throughput Toxicity Assays.Chemical and in vitro biological information to predict mouse liver toxicity using recursive random forests.Integrative chemical-biological read-across approach for chemical hazard classification.Assessment of the DNA damaging potential of environmental chemicals using a quantitative high-throughput screening approach to measure p53 activation.QSAR and Molecular Modeling Approaches for Prediction of Drug MetabolismModelling compound cytotoxicity using conformal prediction and PubChem HTS data
P2860
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P2860
Use of in vitro HTS-derived concentration-response data as biological descriptors improves the accuracy of QSAR models of in vivo toxicity.
description
2010 nî lūn-bûn
@nan
2010 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2010 թվականի հոտեմբերին հրատարակված գիտական հոդված
@hy
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
name
Use of in vitro HTS-derived co ...... AR models of in vivo toxicity.
@ast
Use of in vitro HTS-derived co ...... AR models of in vivo toxicity.
@en
type
label
Use of in vitro HTS-derived co ...... AR models of in vivo toxicity.
@ast
Use of in vitro HTS-derived co ...... AR models of in vivo toxicity.
@en
prefLabel
Use of in vitro HTS-derived co ...... AR models of in vivo toxicity.
@ast
Use of in vitro HTS-derived co ...... AR models of in vivo toxicity.
@en
P2093
P2860
P356
P1476
Use of in vitro HTS-derived co ...... AR models of in vivo toxicity.
@en
P2093
Alexander Sedykh
Ann Richard
Ivan Rusyn
Liying Zhang
P2860
P304
P356
10.1289/EHP.1002476
P577
2010-10-27T00:00:00Z