Band 6
Pharmaceutical Data Mining: Approaches and Applications for Drug Discovery Approaches and Applications for Drug Discovery
Aus der Reihe
Technologies for the Pharmaceutical Industry
185,99 €
inkl. gesetzl. MwSt.,
Lieferung nach Hause
Beschreibung
Produktdetails
Einband
Gebundene Ausgabe
Erscheinungsdatum
01.12.2009
Herausgeber
Sean EkinsVerlag
John Wiley & Sons IncSeitenzahl
562
Maße (L/B/H)
23,6/15,7/2,8 cm
Gewicht
907 g
Auflage
1. Auflage
Reihe
Wiley Series on Technologies for the PharmaceuticalSprache
Englisch
ISBN
978-0-470-19608-3
Leading experts illustrate how sophisticated computational data mining techniques can impact contemporary drug discovery and development
In the era of post-genomic drug development, extracting and applying knowledge from chemical, biological, and clinical data is one of the greatest challenges facing the pharmaceutical industry. Pharmaceutical Data Mining brings together contributions from leading academic and industrial scientists, who address both the implementation of new data mining technologies and application issues in the industry. This accessible, comprehensive collection discusses important theoretical and practical aspects of pharmaceutical data mining, focusing on diverse approaches for drug discovery--including chemogenomics, toxicogenomics, and individual drug response prediction. The five main sections of this volume cover:
* A general overview of the discipline, from its foundations to contemporary industrial applications
* Chemoinformatics-based applications
* Bioinformatics-based applications
* Data mining methods in clinical development
* Data mining algorithms, technologies, and software tools, with emphasis on advanced algorithms and software that are currently used in the industry or represent promising approaches
In one concentrated reference, Pharmaceutical Data Mining reveals the role and possibilities of these sophisticated techniques in contemporary drug discovery and development. It is ideal for graduate-level courses covering pharmaceutical science, computational chemistry, and bioinformatics. In addition, it provides insight to pharmaceutical scientists, principal investigators, principal scientists, research directors, and all scientists working in the field of drug discovery and development and associated industries.
In the era of post-genomic drug development, extracting and applying knowledge from chemical, biological, and clinical data is one of the greatest challenges facing the pharmaceutical industry. Pharmaceutical Data Mining brings together contributions from leading academic and industrial scientists, who address both the implementation of new data mining technologies and application issues in the industry. This accessible, comprehensive collection discusses important theoretical and practical aspects of pharmaceutical data mining, focusing on diverse approaches for drug discovery--including chemogenomics, toxicogenomics, and individual drug response prediction. The five main sections of this volume cover:
* A general overview of the discipline, from its foundations to contemporary industrial applications
* Chemoinformatics-based applications
* Bioinformatics-based applications
* Data mining methods in clinical development
* Data mining algorithms, technologies, and software tools, with emphasis on advanced algorithms and software that are currently used in the industry or represent promising approaches
In one concentrated reference, Pharmaceutical Data Mining reveals the role and possibilities of these sophisticated techniques in contemporary drug discovery and development. It is ideal for graduate-level courses covering pharmaceutical science, computational chemistry, and bioinformatics. In addition, it provides insight to pharmaceutical scientists, principal investigators, principal scientists, research directors, and all scientists working in the field of drug discovery and development and associated industries.
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