Pharmaceutical Data Mining: Approaches and Applications for Drug Discovery
Wiley (November 15, 2004) | 565 pages | 0470196084 | PDF | 6.47 MB
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
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
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