Band 6
Pharmaceutical Data Mining Approaches and Applications for Drug Discovery
Aus der Reihe
Technologies for the Pharmaceutical Industry
145,99 €
inkl. gesetzl. MwSt.Beschreibung
Produktdetails
Format
Kopierschutz
Ja
Family Sharing
Nein
Text-to-Speech
Nein
Erscheinungsdatum
19.11.2009
Verlag
John Wiley & Sons IncSeitenzahl
584 (Printausgabe)
Dateigröße
9739 KB
Auflage
1. Auflage
Sprache
Englisch
EAN
9780470567616
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.
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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