Pharmaceutical Data Mining: Approaches and Applications for Drug Discovery

Pharmaceutical Data Mining: Approaches and Applications for Drug Discovery

Editor(s): Konstantin V. Balakin

Published Online: 1 DEC 2009

Print ISBN: 9780470196083

Online ISBN: 9780470567623

DOI: 10.1002/9780470567623

About this Book

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.

Table of contents

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    1. You have free access to this content
  1. Part I: Data Mining in the Pharmaceutical Industry: A General Overview

  2. Part II: Chemoinformatics - Based Applications

    1. Chapter 7

      Mining High-Throughput Screening Data by Novel Knowledge-Based Optimization Analysis (pages 205–233)

      S. Frank Yan, Frederick J. King, Sumit K. Chanda, Jeremy S. Caldwell, Elizabeth A. Winzeler and Yingyao Zhou

  3. Part III: Bioinformatics - Based Applications

  4. Part IV: Data Mining Methods in Clinical Development

  5. Part V: Data Mining Algorithms and Technologies

    1. You have free access to this content