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Pharmaceutical Data Mining Approaches And Applications For Drug Discovery Konstantin V Balakin

  • SKU: BELL-57672036
Pharmaceutical Data Mining Approaches And Applications For Drug Discovery Konstantin V Balakin
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Pharmaceutical Data Mining Approaches And Applications For Drug Discovery Konstantin V Balakin instant download after payment.

Publisher: John Wiley & Sons, Inc.
File Extension: PDF
File size: 4.63 MB
Author: KONSTANTIN V. BALAKIN
ISBN: 9780470196083, 0470196084
Language: English
Year: 2010

Product desciption

Pharmaceutical Data Mining Approaches And Applications For Drug Discovery Konstantin V Balakin by Konstantin V. Balakin 9780470196083, 0470196084 instant download after payment.

Print ISBN:9780470196083 |Online ISBN:9780470567623 |DOI:10.1002/9780470567623
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.

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