Editors:
- Genetically-engineered mouse models for cancer research have become invaluable tools for studying cancer biology and evaluating novel therapeutic approaches
- This volume focuses on state-of-the-art methods for generating, analyzing and validating such models for studying aspects of human cancer biology
- Additionally, these models are emerging as important pre-clinical systems in which to test cancer prevention and therapeutic strategies in order to select compounds for testing in clinical trials
- Includes supplementary material: sn.pub/extras
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Table of contents (28 chapters)
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Front Matter
About this book
Genetically-engineered mouse models for cancer research have become invaluable tools for studying cancer biology and evaluating novel therapeutic approaches. This volume focuses on state-of-the-art methods for generating, analyzing and validating such models for studying aspects of human cancer biology. Additionally, these models are emerging as important pre-clinical systems in which to test cancer prevention and therapeutic strategies in order to select compounds for testing in clinical trials.
Editors and Affiliations
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, Laboratory Of Cancer Biology and Genetic, National Cancer Institute, Bethesda, USA
Jeffrey E. Green
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National Cancer Institute, Center for Cancer Research, National Institutes of Health, Bethesda, USA
Thomas Ried
Bibliographic Information
Book Title: Genetically Engineered Mice for Cancer Research
Book Subtitle: design, analysis, pathways, validation and pre-clinical testing
Editors: Jeffrey E. Green, Thomas Ried
DOI: https://doi.org/10.1007/978-0-387-69805-2
Publisher: Springer New York, NY
eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)
Copyright Information: Springer Science+Business Media, LLC 2012
Hardcover ISBN: 978-0-387-69803-8
Softcover ISBN: 978-1-4899-9125-6
eBook ISBN: 978-0-387-69805-2
Edition Number: 1
Number of Pages: XX, 632
Topics: Cancer Research, Human Genetics, Laboratory Medicine, Medical Microbiology, Animal Biochemistry, Parasitology