Nicolotti Computational Toxicology
Erscheinungsjahr 2018
ISBN: 978-1-4939-7899-1
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark
Methods and Protocols
E-Book, Englisch, 587 Seiten
Reihe: Springer Protocols
ISBN: 978-1-4939-7899-1
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark
Comprehensive and cutting-edge, Computational Toxicology: Methods and Protocols is a valuable resource for researchers who are interested in learning more about this expanding field.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Weitere Infos & Material
Molecular Descriptors For Structure-Activity Applications: A Hands-On Approach.- The OECD QSAR Toolbox Starts Its Second Decade.- QSAR: What Else? .- (Q)SARs as Adaptations to REACH Information Requirements.- Machine Learning Methods In Computational Toxicology.- Applicability Domain: A Step Toward Confident Predictions And Decidability for QSAR Modeling.- Molecular Similarity In Computational Toxicology.- Molecular Docking for Predictive Toxicology.- Criteria and Application on the use of Non-Testing Methods within a Weight of Evidence Strategy.- Characterization and Management of Uncertainties in Toxicological Risk Assessment: Examples from the Opinions of the European Food Safety Authority.- Computational Toxicology and Drug Discovery.- Approaching Pharmacological Space: Events and Components.- Computational Toxicology Methods in Chemical Library Design and High-Throughput Screening Hit Validation.- Enalos Suite:New Cheminformatics Platform for Drug Discovery and Computational Toxicology.- Ion Channels In Drug Discovery and Safety Pharmacology.- Computational Approaches in Multi-Target Drug Discovery.- Nano-Formulations for Drug Delivery: Safety, Toxicity, and Efficacy.- Toxicity Potential Of Nutraceuticals.- Impact of Pharmaceuticals on the Environment: Risk Assessment using QSAR Modeling Approach.- (Q)SAR Methods for Predicting Genotoxicity and Carcinogenicity: Scientific Rationale and Regulatory Frameworks.- Stem Cell-Based Methods to Predict Developmental Chemical Toxicity.- Predicting Chemically-Induced Skin Sensitisation by using In Chemico/In Vitro Methods.- Hepatotoxicity Prediction by Systems Biology Modeling of Disturbed Metabolic Pathways using Gene Expression Data.- Non-Test Methods to Predict Acute Toxicity: State of Art for Applications of In Silico Methods.- Predictive Systems Toxicology.- Chemoinformatic Approach to Assess Toxicity of Ionic Liquids.- Prediction of Biochemical Endpoints by the CORAL Software: Prejudices, Paradoxes, and Results.




