Advances in QSAR Modeling

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 inthe 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.