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QSAR and SPECTRAL-SAR in Computational Ecotoxicology (Paperback) Loot Price: R2,420
Discovery Miles 24 200
QSAR and SPECTRAL-SAR in Computational Ecotoxicology (Paperback): Mihai V. Putz

QSAR and SPECTRAL-SAR in Computational Ecotoxicology (Paperback)

Mihai V. Putz

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Loot Price R2,420 Discovery Miles 24 200 | Repayment Terms: R227 pm x 12*

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QSAR and SPECTRAL-SAR in Computational Ecotoxicology presents a collection of studies based on the epistemological bulk data-information-knowledge of the chemicals used in green chemistry. It assesses a specific model of pattern characterization of concerned active substances at the bio-, eco-, and pharmacologic levels through unitary formulation of the effector-receptor binding degree potential, including the logistic type by employing a computational algebraic quantitative structure-activity relationship (QSAR) model called SPECTRAL-SAR. It aims to minimize the residual recorded activities in the experiments that study the enzymic, ionic liquid, antagonists, and allosteric inhibition interactions. The book covers: The classic QSAR approach The new SPECTRAL-SAR approach How to draw SPECTRAL-SAR maps for predicting ecotoxicological mechanisms for a given series of toxicants and single or multi-species in an open system Biological activity as related to chemical reactivity through associate descriptors This book will be very useful in advanced courses on computational ecotoxicology, drug design and interaction, methods in quantum and computational chemistry, chemical molding, chemical bonding, and others.

General

Imprint: Apple Academic Press Inc.
Country of origin: Canada
Release date: March 2021
First published: 2012
Editors: Mihai V. Putz
Dimensions: 234 x 156mm (L x W)
Format: Paperback
Pages: 242
ISBN-13: 978-1-77463-202-4
Categories: Books > Medicine > Other branches of medicine > Environmental medicine > General
Books > Science & Mathematics > Chemistry > Physical chemistry > General
Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues > General
LSN: 1-77463-202-0
Barcode: 9781774632024

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