Description

Book Synopsis
The book covers theoretical background and methodology as well as all current applications of Quantitative Structure-Activity Relationships (QSAR). Written by an international group of recognized researchers, this edited volume discusses applications of QSAR in multiple disciplines such as chemistry, pharmacy, environmental and agricultural sciences addressing data gaps and modern regulatory requirements. Additionally, the applications of QSAR in food science and nanoscience have been included – two areas which have only recently been able to exploit this versatile tool. This timely addition to the series is aimed at graduate students, academics and industrial scientists interested in the latest advances and applications of QSAR.



Table of Contents
Performance parameters and validation practices in QSAR modeling.- Towards interpretable QSAR models.- The use of topological indices in QSAR and QSPR modeling.- The Maximum Common Substructure (MCS) search as a new tool for SAR and QSAR.- The universal approach for structural and physico-chemical interpretation of QSAR/QSPR models.- Generative Topographic Mapping approach.- Monte Carlo methods for solution of tasks in Environmental Sciences.- QSAR in Environmental Research.- QSAR applications for environmental chemical prioritization: Biotransformation of chemicals.- QSAR modeling in environmental risk assessment: application to the prediction of pesticide toxicity.- Counter propagation artificial neural network (CP ANN) models for prediction of carcinogenicity of non congeneric chemicals for regulatory uses.- Strategy for identification of critical nanomaterials properties linked to biological impacts: interlinking of experimental and computational approaches.- QSAR/QSPR modeling in the design of drug candidates with balanced pharmacodynamics and pharmacokinetic properties.- Molecular modeling of food chemicals as potential bioactive compounds.- On application QSARs in Food and Agricultural Sciences: History and Recent Developments.

Advances in QSAR Modeling: Applications in

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A Paperback / softback by Kunal Roy

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    View other formats and editions of Advances in QSAR Modeling: Applications in by Kunal Roy

    Publisher: Springer International Publishing AG
    Publication Date: 02/08/2018
    ISBN13: 9783319860183, 978-3319860183
    ISBN10: 3319860186

    Description

    Book Synopsis
    The book covers theoretical background and methodology as well as all current applications of Quantitative Structure-Activity Relationships (QSAR). Written by an international group of recognized researchers, this edited volume discusses applications of QSAR in multiple disciplines such as chemistry, pharmacy, environmental and agricultural sciences addressing data gaps and modern regulatory requirements. Additionally, the applications of QSAR in food science and nanoscience have been included – two areas which have only recently been able to exploit this versatile tool. This timely addition to the series is aimed at graduate students, academics and industrial scientists interested in the latest advances and applications of QSAR.



    Table of Contents
    Performance parameters and validation practices in QSAR modeling.- Towards interpretable QSAR models.- The use of topological indices in QSAR and QSPR modeling.- The Maximum Common Substructure (MCS) search as a new tool for SAR and QSAR.- The universal approach for structural and physico-chemical interpretation of QSAR/QSPR models.- Generative Topographic Mapping approach.- Monte Carlo methods for solution of tasks in Environmental Sciences.- QSAR in Environmental Research.- QSAR applications for environmental chemical prioritization: Biotransformation of chemicals.- QSAR modeling in environmental risk assessment: application to the prediction of pesticide toxicity.- Counter propagation artificial neural network (CP ANN) models for prediction of carcinogenicity of non congeneric chemicals for regulatory uses.- Strategy for identification of critical nanomaterials properties linked to biological impacts: interlinking of experimental and computational approaches.- QSAR/QSPR modeling in the design of drug candidates with balanced pharmacodynamics and pharmacokinetic properties.- Molecular modeling of food chemicals as potential bioactive compounds.- On application QSARs in Food and Agricultural Sciences: History and Recent Developments.

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