Cancer Gene Profiling (eBook, PDF)

Methods and Protocols
Redaktion: Grützmann, Robert; Pilarsky, Christian

• Format: PDF

Produktbeschreibung

This second edition volume brings together the experiences of leading scientists in the discipline of cancer gene profiling. Because cancer genes can be profiled in many different ways, Cancer Gene Profiling: Methods and Protocols, Second Edition explores different techniques and approaches needed to understand the key stages of cancer development, as using only one technique would be insufficient. This book provides readers with an overview of the state-of-the-art methods that will enable them to perform these experiments, and demonstrates the kind of analysis that is possible in our current biomedical research. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.

Thorough and cutting-edge, Cancer Gene Profiling: Methods and Protocols, Second Edition is a great resource for any student or practitioner with an interest in cancer gene profiling, and can be used in any well-equipped research laboratory.

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Produktdetails

• Verlag: Springer New York
• Seitenzahl: 256
• Erscheinungstermin: 14. Dezember 2015
• Englisch
• ISBN-13: 9781493932047
• Artikelnr.: 64692072

Inhaltsangabe

Factors Affecting the Use of Human Tissues in Biomedical Research: Implications in the Design and Operation of a Biorepository.- Tissue Microdissection.- Tissue Microarrays.- Gene Expression Analysis in the Age of Mass Sequencing: An Introduction.- Quantitative DNA Methylation in Cancer.- Single Nucleotide Polymorphism to Associate Cancer Risk.- Exosomes in Cancer Disease.- MicroRNAs (miRNAs) Profiling.- Cancer Gene Profiling for Response Prediction.- Target Gene Discovery for Novel Therapeutic Agents in Cancer Treatment.- Application of Proteomics in Cancer Biomarker Discovery: GeLC-MS/MS.- Meta-Analysis of Cancer Gene Profiling Data.- Reproducible, Scalable Fusion Gene Detection from RNA-Seq.- Transcriptome Sequencing for the Detection of Chimeric Transcripts.