Text Mining for Genomics-based Drug Discovery - Couverture souple

Herron, Patrick

 
9783836437141: Text Mining for Genomics-based Drug Discovery

Synopsis

While many text mining projects emphasize retrieval and extraction, text mining can be leveraged to discover new and previously unknown infor-mation. Nowhere is the potential more apparent than in pharmacogenomics-based drug discovery. Text mining can help pharmaceutical researchers reduce the vast information overload hindering pharmacogenomics-based drug discovery because it can aid in the generation of rich novel information from large collections of diverse scientific literature and research data. However the pharmaceutical industry appears to be reluctant to innovate bleeding-edge text mining technologies for drug discovery. The present book re-frames text mining as an approach to automate the generation of novel and interesting information, reviews successful exemplary text mining appli-cations, and examines a case study of a leading pharma-ceutical company within the book's proposed novelty-generation paradigm. The present book is written for a wide range of professionals and scholars, not only for infor-mation scientists, industry analysts, and pharmaceutical executives, but also for those interested in innovation studies and the automated acceleration of discovery.

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Présentation de l'éditeur

Revision with unchanged content. While many text mining projects emphasize retrieval and extraction, text mining can be leveraged to discover new and previously unknown infor­mation. Nowhere is the potential more apparent than in pharmacogenomics-based drug discovery. Text mining can help pharmaceutical researchers reduce the vast information overload hindering pharmacogenomics-based drug discovery because it can aid in the generation of rich novel information from large collections of diverse scientific literature and research data. However the pharmaceutical industry appears to be reluctant to innovate bleeding-edge text mining technologies for drug discovery. The present book re-frames text mining as an approach to automate the generation of novel and interesting information, reviews successful exemplary text mining appli­cations, and examines a case study of a leading pharma­ceutical company within the book’s proposed novelty-generation paradigm. The present book is written for a wide range of professionals and scholars, not only for infor­mation scientists, industry analysts, and pharmaceutical executives, but also for those interested in innovation studies and the automated acceleration of discovery.

Biographie de l'auteur

The author is Research Analyst and Chief Technologistfor the Jenkins Chair in New Technologies and Society at Duke University.

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Autres éditions populaires du même titre

9783639453393: Text Mining for Genomics-based Drug Discovery

Edition présentée

ISBN 10 :  3639453395 ISBN 13 :  9783639453393
Editeur : AV Akademikerverlag, 2012
Couverture souple