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Bioinformatics and computational bio...

Loging, William T.

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Bioinformatics and computational biology in drug discovery and development

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Bioinformatics and computational biology in drug discovery and development/ edited by William T. Loging.
其他題名:	Bioinformatics & Computational Biology in Drug Discovery & Development
其他作者:	Loging, William T.
出版者:	Cambridge :Cambridge University Press, : 2016.,
面頁冊數:	xi, 233 p. :ill., digital ;24 cm.
內容註:	Machine generated contents note: Foreword; Preface: the future of drug discovery and health care / Eric Schadt; 1. The art and science of the Drug Discovery Pipeline (DDP) / William T. Loging; 2. Computational approaches to drug target identification / Thomas B. Freeman and Pek Lum; 3. Understanding human disease knowledge through text mining / Raul Rodriguez-Esteban; 4. Integrating translational biomarkers into drug development / Jonathan Phillips; 5. Computational phenotypic assessment of small molecules in drug discovery / William T. Loging and Thomas B. Freeman; 6. Data visualization and the DDP process / Ke Xu; 7. Information visualization - important IT considerations / Telmo Silva; 8. The New Drug Application (NDA) and regulatory approval stages / William T. Loging, Marilyn Lewis, Bryn Williams-Jones and Roy Mansfield; 9. Clinical trial failures and drug repositioning / Mark Crawford and Jeff Handler; Appendix I. Additional knowledge-based analysis approaches / Raul Rodriguez-Esteban; Appendix II. Open source tools and public data sources / Yirong Wang and William T. Loging; Index.
標題:	Drug development. -
電子資源:	https://doi.org/10.1017/CBO9780511989421
ISBN:	9780511989421

Bioinformatics and computational biology in drug discovery and development
Bioinformatics and computational biology in drug discovery and development[electronic resource] /Bioinformatics & Computational Biology in Drug Discovery & Developmentedited by William T. Loging. - Cambridge :Cambridge University Press,2016. - xi, 233 p. :ill., digital ;24 cm.

Machine generated contents note: Foreword; Preface: the future of drug discovery and health care / Eric Schadt; 1. The art and science of the Drug Discovery Pipeline (DDP) / William T. Loging; 2. Computational approaches to drug target identification / Thomas B. Freeman and Pek Lum; 3. Understanding human disease knowledge through text mining / Raul Rodriguez-Esteban; 4. Integrating translational biomarkers into drug development / Jonathan Phillips; 5. Computational phenotypic assessment of small molecules in drug discovery / William T. Loging and Thomas B. Freeman; 6. Data visualization and the DDP process / Ke Xu; 7. Information visualization - important IT considerations / Telmo Silva; 8. The New Drug Application (NDA) and regulatory approval stages / William T. Loging, Marilyn Lewis, Bryn Williams-Jones and Roy Mansfield; 9. Clinical trial failures and drug repositioning / Mark Crawford and Jeff Handler; Appendix I. Additional knowledge-based analysis approaches / Raul Rodriguez-Esteban; Appendix II. Open source tools and public data sources / Yirong Wang and William T. Loging; Index.

Computational biology drives discovery through its use of high-throughput informatics approaches. This book provides a road map of the current drug development process and how computational biology approaches play a critical role across the entire drug discovery pipeline. Through the use of previously unpublished, real-life case studies the impact of a range of computational approaches are discussed at various phases of the pipeline. Additionally, a focus section provides innovative visualisation approaches, from both the drug discovery process as well as from other fields that utilise large datasets, recognising the increasing use of such technology. Serving the needs of early career and more experienced scientists, this up-to-date reference provides an essential introduction to the process and background of drug discovery, highlighting how computational researchers can contribute to that pipeline.

ISBN: 9780511989421Subjects--Topical Terms:

716904
Drug development.

LC Class. No.: RM301.25 / .B56 2016

Dewey Class. No.: 615.19

Bioinformatics and computational biology in drug discovery and development
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505 8 $a Machine generated contents note: Foreword; Preface: the future of drug discovery and health care / Eric Schadt; 1. The art and science of the Drug Discovery Pipeline (DDP) / William T. Loging; 2. Computational approaches to drug target identification / Thomas B. Freeman and Pek Lum; 3. Understanding human disease knowledge through text mining / Raul Rodriguez-Esteban; 4. Integrating translational biomarkers into drug development / Jonathan Phillips; 5. Computational phenotypic assessment of small molecules in drug discovery / William T. Loging and Thomas B. Freeman; 6. Data visualization and the DDP process / Ke Xu; 7. Information visualization - important IT considerations / Telmo Silva; 8. The New Drug Application (NDA) and regulatory approval stages / William T. Loging, Marilyn Lewis, Bryn Williams-Jones and Roy Mansfield; 9. Clinical trial failures and drug repositioning / Mark Crawford and Jeff Handler; Appendix I. Additional knowledge-based analysis approaches / Raul Rodriguez-Esteban; Appendix II. Open source tools and public data sources / Yirong Wang and William T. Loging; Index.
520 $a Computational biology drives discovery through its use of high-throughput informatics approaches. This book provides a road map of the current drug development process and how computational biology approaches play a critical role across the entire drug discovery pipeline. Through the use of previously unpublished, real-life case studies the impact of a range of computational approaches are discussed at various phases of the pipeline. Additionally, a focus section provides innovative visualisation approaches, from both the drug discovery process as well as from other fields that utilise large datasets, recognising the increasing use of such technology. Serving the needs of early career and more experienced scientists, this up-to-date reference provides an essential introduction to the process and background of drug discovery, highlighting how computational researchers can contribute to that pipeline.
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