Dabade sapna jain (9 risultati)

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  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2026

    6630121813 / 9786630121810

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    Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US

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    EUR 103,15

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    Quantità: Più di 20 disponibili

    PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

  • Lingua: Inglese

    Editore: LAP Lambert Academic Publishing, 2026

    6630121813 / 9786630121810

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    Da: California Books, Miami, FL, U.S.A.California Books

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    Condizione: Nuovo

    EUR 104,22

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    Quantità: Più di 20 disponibili

    Condizione: New.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2026

    6630121813 / 9786630121810

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    Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK

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    Condizione: Nuovo

    EUR 99,39

    EUR 4,85 spedizione 
    Spedito da Regno Unito a U.S.A.

    Quantità: Più di 20 disponibili

    PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

  • Lingua: Inglese

    Editore: LAP Lambert Academic Publishing, 2026

    6630121813 / 9786630121810

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    • Print on Demand

    Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail

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    Condizione: Nuovo

    EUR 103,14

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    Quantità: 1 disponibili

    Paperback. Condizione: new. Paperback. The book presents an integrated computational approach for antifungal drug discovery targeting N-myristoyltransferase (NMT) in Candida albicans, a promising therapeutic target against antifungal resistance. It highlights the application of computer-aided drug design (CADD) techniques, particularly QSAR modeling using Genetic Algorithm-Stepwise Multiple Linear Regression (GA-SMLR) and molecular docking studies, to identify and optimize novel NMT inhibitors. The study evaluates bisamidine, coumarin, and triazole derivatives, revealing key molecular descriptors, structural features, and binding interactions responsible for antifungal activity. Rigorous internal and external validation ensures the statistical robustness and predictive reliability of the QSAR models. By combining structure-activity relationships with protein-ligand interaction analysis, the book provides valuable insights into rational drug design, lead optimization, and antifungal therapeutic development. It serves as a practical resource for researchers and students in medicinal chemistry, pharmaceutical sciences, computational biology, and antifungal drug discovery. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing Jun 2026, 2026

    6630121813 / 9786630121810

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    Condizione: Nuovo

    EUR 87,90

    EUR 23,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 2 disponibili

    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 188 pp. Englisch.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2026

    6630121813 / 9786630121810

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    Da: preigu, Osnabrück, Germaniapreigu

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    Condizione: Nuovo

    EUR 72,70

    EUR 70,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 5 disponibili

    Taschenbuch. Condizione: Neu. Computer-Aided Antifungal Drug Design | Potential N-Myristoyltransferase (NMT) Inhibitors of Candida albicans | Sapna Jain Dabade (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786630121810 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.

  • Lingua: Inglese

    Editore: LAP Lambert Academic Publishing, 2026

    6630121813 / 9786630121810

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    • Print on Demand

    Da: CitiRetail, Stevenage, Regno UnitoCitiRetail

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    Condizione: Nuovo

    EUR 105,69

    EUR 43,15 spedizione 
    Spedito da Regno Unito a U.S.A.

    Quantità: 1 disponibili

    Paperback. Condizione: new. Paperback. The book presents an integrated computational approach for antifungal drug discovery targeting N-myristoyltransferase (NMT) in Candida albicans, a promising therapeutic target against antifungal resistance. It highlights the application of computer-aided drug design (CADD) techniques, particularly QSAR modeling using Genetic Algorithm-Stepwise Multiple Linear Regression (GA-SMLR) and molecular docking studies, to identify and optimize novel NMT inhibitors. The study evaluates bisamidine, coumarin, and triazole derivatives, revealing key molecular descriptors, structural features, and binding interactions responsible for antifungal activity. Rigorous internal and external validation ensures the statistical robustness and predictive reliability of the QSAR models. By combining structure-activity relationships with protein-ligand interaction analysis, the book provides valuable insights into rational drug design, lead optimization, and antifungal therapeutic development. It serves as a practical resource for researchers and students in medicinal chemistry, pharmaceutical sciences, computational biology, and antifungal drug discovery. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing Jun 2026, 2026

    6630121813 / 9786630121810

    • Brossura
    • Print on Demand

    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Condizione: Nuovo

    EUR 87,90

    EUR 60,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 1 disponibili

    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book presents an integrated computational approach for antifungal drug discovery targeting N-myristoyltransferase (NMT) in Candida albicans, a promising therapeutic target against antifungal resistance. It highlights the application of computer-aided drug design (CADD) techniques, particularly QSAR modeling using Genetic Algorithm-Stepwise Multiple Linear Regression (GA-SMLR) and molecular docking studies, to identify and optimize novel NMT inhibitors. The study evaluates bisamidine, coumarin, and triazole derivatives, revealing key molecular descriptors, structural features, and binding interactions responsible for antifungal activity. Rigorous internal and external validation ensures the statistical robustness and predictive reliability of the QSAR models. By combining structure-activity relationships with protein-ligand interaction analysis, the book provides valuable insights into rational drug design, lead optimization, and antifungal therapeutic development. It serves as a practical resource for researchers and students in medicinal chemistry, pharmaceutical sciences, computational biology, and antifungal drug discovery. 188 pp. Englisch.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2026

    6630121813 / 9786630121810

    • Brossura
    • Print on Demand

    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    Condizione: Nuovo

    EUR 212,85

    EUR 30,50 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 2 disponibili

    Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The book presents an integrated computational approach for antifungal drug discovery targeting N-myristoyltransferase (NMT) in Candida albicans, a promising therapeutic target against antifungal resistance. It highlights the application of computer-aided drug design (CADD) techniques, particularly QSAR modeling using Genetic Algorithm-Stepwise Multiple Linear Regression (GA-SMLR) and molecular docking studies, to identify and optimize novel NMT inhibitors. The study evaluates bisamidine, coumarin, and triazole derivatives, revealing key molecular descriptors, structural features, and binding interactions responsible for antifungal activity. Rigorous internal and external validation ensures the statistical robustness and predictive reliability of the QSAR models. By combining structure-activity relationships with protein-ligand interaction analysis, the book provides valuable insights into rational drug design, lead optimization, and antifungal therapeutic development. It serves as a practical resource for researchers and students in medicinal chemistry, pharmaceutical sciences, computational biology, and antifungal drug discovery.