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Gene Expression Profiling by Microarrays: Clinical Implications

Gene Expression Profiling by Microarrays: Clinical Implications

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Cambridge University Press, 6/22/2006
EAN 9780521853965, ISBN10: 0521853966

Hardcover, 262 pages, 25.3 x 18 x 1.8 cm
Language: English

Microarray analysis is a highly efficient tool for assessing the expression of a large number of genes simultaneously, and offers a new means to classify cancer and other diseases. Gene expression profiling can also be used to predict clinical outcome and response to specific therapeutic agents. This survey spans recent applications of microarrays in clinical medicine, covering malignant disease including acute leukaemias, lymphoid malignancies and breast cancer, together with diabetes and heart disease. Investigators in oncology, pharmacology and related clinical sciences, as well as basic scientists, will value this review of a promising new diagnostic and prognostic technology.

Preface Eckhard Thiel
1. Introduction Wolf-Karsten Hofmann
2. Technique of microarrays
microarray platforms Sven de Vos
3. Quantitative quality control of microarray experiments
toward accurate gene expression measurements Xujing Wang and Martin J. Hessner
4. Statistical analysis of gene expression data David A. Elashoff
5. Genomic stratification in patients with heart failure Tara A. Bullard, Frédérick Aguilar, Jennifer L. Hall and Burns C. Blaxall
6. Gene expression profiling for the diagnosis of acute leukemias Torsten Haferlach, Alexander Kohlmann, Susanne Schnittger, Claudia Schoch and Wolfgang Kern
7. Gene expression profiling can distinguish tumour subclasses of breast carcinomas Ingrid A. Hedenfalk
8. Gene expression profiling in lymphoid malignancies Christof Burek, Elena Hartmann, Zhengrong Mao, German Ott and Andreas Rosenwald
9. MRNA profiling of pancreatic beta cells
investigating mechanisms of diabetes Leentje Van Lommel, Yves Moreau, Daniel Pipeleers, Jean-Christophe Jonas and Frans Schuit
10. Prediction of response and resistance to treatment by gene expression profiling Philipp Kiewe and Wolf-Karsten Hofmann.