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Añadir al carritoHardcover. Condición: new. Hardcover. Drug discovery has evolved from empirical experimentation into a data-driven, computation-intensive discipline, yet challenges of high attrition, rising costs, and translational failure persist. Addressing this complexity demands a mechanistic and predictive approach to molecular design.Computer-Aided Drug Design: Principles, Methods, and Applications in Drug Discovery presents a rigorous and integrated framework for modern CADD, encompassing molecular modeling, QSAR, docking, molecular dynamics, virtual screening, pharmacophore modeling, and fragment-based design. Rather than isolating techniques, the text connects algorithms, physicochemical principles, and biological systems to explain how computational methods guide rational drug development .Designed for postgraduate pharmacy students, doctoral researchers, and professionals, the book delivers conceptual clarity and algorithmic understanding while supporting structured academic responses and practical workflow competence.Its distinguishing strength lies in mechanistic depth and decision-focused reasoning-each method is examined in terms of its assumptions, parameter sensitivity, and real-world applicability, bridging computational prediction with pharmaceutical relevance.As drug discovery increasingly integrates artificial intelligence and large-scale data, this work provides a clear intellectual pathway to navigate and advance the future of rational therapeutic design. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Añadir al carritoHardcover. Condición: new. Hardcover. Drug discovery has evolved from empirical experimentation into a data-driven, computation-intensive discipline, yet challenges of high attrition, rising costs, and translational failure persist. Addressing this complexity demands a mechanistic and predictive approach to molecular design.Computer-Aided Drug Design: Principles, Methods, and Applications in Drug Discovery presents a rigorous and integrated framework for modern CADD, encompassing molecular modeling, QSAR, docking, molecular dynamics, virtual screening, pharmacophore modeling, and fragment-based design. Rather than isolating techniques, the text connects algorithms, physicochemical principles, and biological systems to explain how computational methods guide rational drug development .Designed for postgraduate pharmacy students, doctoral researchers, and professionals, the book delivers conceptual clarity and algorithmic understanding while supporting structured academic responses and practical workflow competence.Its distinguishing strength lies in mechanistic depth and decision-focused reasoning-each method is examined in terms of its assumptions, parameter sensitivity, and real-world applicability, bridging computational prediction with pharmaceutical relevance.As drug discovery increasingly integrates artificial intelligence and large-scale data, this work provides a clear intellectual pathway to navigate and advance the future of rational therapeutic design. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Librería: AussieBookSeller, Truganina, VIC, Australia
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Añadir al carritoHardcover. Condición: new. Hardcover. Drug discovery has evolved from empirical experimentation into a data-driven, computation-intensive discipline, yet challenges of high attrition, rising costs, and translational failure persist. Addressing this complexity demands a mechanistic and predictive approach to molecular design.Computer-Aided Drug Design: Principles, Methods, and Applications in Drug Discovery presents a rigorous and integrated framework for modern CADD, encompassing molecular modeling, QSAR, docking, molecular dynamics, virtual screening, pharmacophore modeling, and fragment-based design. Rather than isolating techniques, the text connects algorithms, physicochemical principles, and biological systems to explain how computational methods guide rational drug development .Designed for postgraduate pharmacy students, doctoral researchers, and professionals, the book delivers conceptual clarity and algorithmic understanding while supporting structured academic responses and practical workflow competence.Its distinguishing strength lies in mechanistic depth and decision-focused reasoning-each method is examined in terms of its assumptions, parameter sensitivity, and real-world applicability, bridging computational prediction with pharmaceutical relevance.As drug discovery increasingly integrates artificial intelligence and large-scale data, this work provides a clear intellectual pathway to navigate and advance the future of rational therapeutic design. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Publicado por Notion Press, 2026
ISBN 13: 9798903928408
Librería: preigu, Osnabrück, Alemania
EUR 95,15
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Añadir al carritoBuch. Condición: Neu. Computer-Aided Drug Design | Principles, Methods, and Applications in Drug Discovery | Saravanan (u. a.) | Buch | Englisch | 2026 | Notion Press | EAN 9798903928408 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Publicado por Notion Press
ISBN 13: 9798903928408
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 109,30
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Añadir al carritoBuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Drug discovery has evolved from empirical experimentation into a data-driven, computation-intensive discipline, yet challenges of high attrition, rising costs, and translational failure persist. Addressing this complexity demands a mechanistic and predictive approach to molecular design.Computer-Aided Drug Design: Principles, Methods, and Applications in Drug Discovery presents a rigorous and integrated framework for modern CADD, encompassing molecular modeling, QSAR, docking, molecular dynamics, virtual screening, pharmacophore modeling, and fragment-based design. Rather than isolating techniques, the text connects algorithms, physicochemical principles, and biological systems to explain how computational methods guide rational drug development .Designed for postgraduate pharmacy students, doctoral researchers, and professionals, the book delivers conceptual clarity and algorithmic understanding while supporting structured academic responses and practical workflow competence.Its distinguishing strength lies in mechanistic depth and decision-focused reasoning-each method is examined in terms of its assumptions, parameter sensitivity, and real-world applicability, bridging computational prediction with pharmaceutical relevance.As drug discovery increasingly integrates artificial intelligence and large-scale data, this work provides a clear intellectual pathway to navigate and advance the future of rational therapeutic design.