Advances in QSAR Modeling, 1st ed. 2017 Applications in Pharmaceutical, Chemical, Food, Agricultural and Environmental Sciences Challenges and Advances in Computational Chemistry and Physics Series, Vol. 24

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.

Prof. Dr. Kunal Roy is a Professor of the Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology Jadavpur University, Kolkata India. He was previously a Marie Curie International Incoming Fellow and Commonwealth Academic Staff Fellow at the University of Manchester, UK. Prof. Roy has published over 240 articles in peer reviewed journals, two books, one edited book as well as ten book chapters.