{"product_id":"computational-toxicology-9781071640029","title":"Computational Toxicology","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eQSAR: Using the Past to Study the Present.- Molecular similarity in predictive toxicology with a focus on the q-RASAR technique.- Weight of Evidence: criteria and applications.- Integration of QSAR and NAM in the Read Across process for an effective and relevant toxicological assessment.- Automated workflows for data curation and machine learning to develop Quantitative Structure-Activity Relationships.- Applicability Domain for Trustable Predictions.- The potential of molecular docking for predictive toxicology.- Computational toxicology methods in chemical library design and high-throughput screening hit validation.- Toxicity potential of nutraceuticals.- Development, use and validation of (Q)SARs for predicting genotoxicity and carcinogenicity: experiences from Italian National Institute of Health activities .- Adverse outcome pathways mechanistically describing hepatotoxicity.- Machine learning in early prediction of metabolism of drugs.- In vitro cell-based MTT and Crystal Viol\u003c\/p\u003e","brand":"Humana","offers":[{"title":"Default Title","offer_id":53186414248279,"sku":"9781071640029","price":152.99,"currency_code":"GBP","in_stock":false}],"url":"https:\/\/bookcurl.com\/products\/computational-toxicology-9781071640029","provider":"Book Curl","version":"1.0","type":"link"}