Measuring Gene Expression
Published on 18. April 2008
328 pages
978-1-134-18917-5 (ISBN)
Description
In the post-genomic age, much biomedical research looks at when, where, and at what level genes are expressed. Measuring Gene Expression is an all-in-one introduction to the main methods of measuring gene expression, including RT-PCR, differential display, RNA interference, reporter genes, microarrays, and proteomics, as well as a section on RNA isolation and analysis. There is an overview of each method: its pros and cons, sample preparation, sources of error, and data interpretation.
Reviews / Votes
"This is an excellent book. I wish I had had it a few years ago for my research group. It has all the techniques in one place."Professor Sir Aaron Klug OM FRS
MRC Laboratory of Molecular Biology
Cambridge, UK
More details
Series
Language
English
Place of publication
London
United Kingdom
Target group
College/higher education
Professional and scholarly
Product notice
Reflowable
Illustrations
81 s/w Abbildungen, 11 s/w Tabellen, 81 s/w Zeichnungen
11 Tables, black and white; 81 Line drawings, black and white; 81 Illustrations, black and white
File size
3,41 MB
ISBN-13
978-1-134-18917-5 (9781134189175)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Matthew Avison
Measuring Gene Expression
Book
07/2006
1st Edition
Taylor & Francis
€119.12
Article not available at the moment
Person
Matthew Avison, Department of Pathology and Microbiology, School of Medical Sciences, University of Bristol, UK
Content
1. Gene Expression and its Control 2. Isolation and Analysis of RNA 3. Hybridization-based Methods for Measuring Transcript Levels 4. PCR-based Methods for Measuring Transcript Levels 5. Differential Display, Subtractive Hybridization, Amplification Suppression and SAGE Techniques for Measuring Gene Expression 6. Measuring Gene Expression Using Reporter Gene Assays 7. Analysis of the Proteome 8. Statistical Analysis of Gene Expression Data
