Imagen de Google Jackets

Computational Toxicology Methods and Protocols / edited by Orazio Nicolotti.

Colaborador(es): Nicolotti, Orazio, editor literario.
Series (Methods in Molecular Biology, 1940-6029; 1800).Editor: New York, NY : Springer International Publishing, 2018Edición: 1st edition 2018.Descripción: 1 recurso en línea (XVI, 587 páginas) : 177 ilustraciones, 115 ilustraciones a color.ISBN: 9781493978991.Recursos en línea: (usuarios Universidad Europea de Valencia)Digital Resources
Contenidos:
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.
Resumen: This volume explores techniques that are currently used to understand solid target-specific models in computational toxicology. The chapters are divided into four sections and discuss topics such as molecular descriptors, QSAR and read-across; molecular and data modeling techniques to comply both with scientific and regulatory sides; computational toxicology in drug discovery; and strategies on how to predict various human-health toxicology endpoints. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the methods and software tools used, step-by-step, readily reproducible computational protocols, and tips on troubleshooting and avoiding known pitfalls. 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.
Valoración
    Valoración media: 0.0 (0 votos)
Existencias
Tipo de ítem Biblioteca actual Signatura topográfica Estado Fecha de vencimiento Código de barras Reserva de ítems
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Valencia Digital Acceso Electrónico (UEV) Acceso electrónico eBook.20123020
Total de reservas: 0

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.

This volume explores techniques that are currently used to understand solid target-specific models in computational toxicology. The chapters are divided into four sections and discuss topics such as molecular descriptors, QSAR and read-across; molecular and data modeling techniques to comply both with scientific and regulatory sides; computational toxicology in drug discovery; and strategies on how to predict various human-health toxicology endpoints. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the methods and software tools used, step-by-step, readily reproducible computational protocols, and tips on troubleshooting and avoiding known pitfalls. 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.

No hay comentarios en este titulo.

para colocar un comentario.
Compartir