Text Mining for Genomics-based Drug Discovery

Patrick Herron

ISBN 10: 3836437147 / ISBN 13: 9783836437141

Published by VDM Verlag Dr. Müller Mai 2008, 2008

About this Item

Neuware - 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 moreapparent 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.

Seller Inventory # 9783836437141

Bibliographic Details

• Title: Text Mining for Genomics-based Drug Discovery
• Publisher: VDM Verlag Dr. Müller Mai 2008
• Publication Date: 2008
• Language: English
• ISBN 10: 3836437147
• ISBN 13: 9783836437141
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 24W x 0H x 0D centimeters 24 centimeters width by 0 centimeters height by 0 centimeters depth
• Weight: 205 grams

About this title

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.

About the Author

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