Patient-Derived Xenograft Models of Human Cancer

Nonfiction, Health & Well Being, Medical, Specialties, Oncology
Cover of the book Patient-Derived Xenograft Models of Human Cancer by , Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9783319558257
Publisher: Springer International Publishing Publication: June 27, 2017
Imprint: Humana Language: English
Author:
ISBN: 9783319558257
Publisher: Springer International Publishing
Publication: June 27, 2017
Imprint: Humana
Language: English

This book provides a comprehensive, state-of-the-art review of PDX cancer models. In separately produced chapters, the history and evolution of PDX models is reviewed, methods of PDX model development are compared in detail, characteristics of available established models are presented, current applications are summarized and new perspectives about use of PDX models are proposed. Each chapter is written by a world-renowned expert who is conducting cutting-edge research in the field. Each of the subsections provide a comprehensive review of existing literature addressing the particular topic followed by a conclusive paragraph detailing future directions. Extensive illustrations make this an interactive text. 

Patient-Derived Xenograft Models of Human Cancer will serve as a highly useful resource for researchers and clinicians dealing with, or interested in, this important topic. It will provide a concise yet comprehensive summary of the current status of the field that will help guide preclinical and clinical applications as well as stimulate investigative efforts. This book will propagate innovative concepts and prompt the development of ground-breaking technological solutions in this field.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This book provides a comprehensive, state-of-the-art review of PDX cancer models. In separately produced chapters, the history and evolution of PDX models is reviewed, methods of PDX model development are compared in detail, characteristics of available established models are presented, current applications are summarized and new perspectives about use of PDX models are proposed. Each chapter is written by a world-renowned expert who is conducting cutting-edge research in the field. Each of the subsections provide a comprehensive review of existing literature addressing the particular topic followed by a conclusive paragraph detailing future directions. Extensive illustrations make this an interactive text. 

Patient-Derived Xenograft Models of Human Cancer will serve as a highly useful resource for researchers and clinicians dealing with, or interested in, this important topic. It will provide a concise yet comprehensive summary of the current status of the field that will help guide preclinical and clinical applications as well as stimulate investigative efforts. This book will propagate innovative concepts and prompt the development of ground-breaking technological solutions in this field.

More books from Springer International Publishing

Cover of the book Fixed Point Theory in Modular Function Spaces by
Cover of the book The Sociology of Everyday Life Peacebuilding by
Cover of the book Sensing Vehicle Conditions for Detecting Driving Behaviors by
Cover of the book Data Mining and Big Data by
Cover of the book Giovanni Domenico Cassini by
Cover of the book Schizoanalytic Ventures at the End of the World by
Cover of the book Information Security Theory and Practice by
Cover of the book Modeling, Analysis, and Visualization of Anisotropy by
Cover of the book Russia's Border Wars and Frozen Conflicts by
Cover of the book Mathematical Modeling of Protein Complexes by
Cover of the book The Significance of the Lvov-Warsaw School in the European Culture by
Cover of the book Vegetation History and Cultural Landscapes by
Cover of the book Climate Change Research at Universities by
Cover of the book Theoretical Femtosecond Physics by
Cover of the book Machine Learning and Knowledge Discovery in Databases by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy