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Gene Expression Profiling by Microarrays: Clinical Implications
9780521853965
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Description
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.
Product Details
99133
9780521853965
9780521853965
Data sheet
- Publication date
- 2006
- Issue number
- 1
- Cover
- hard cover
- Pages count
- 262
- Dimensions (mm)
- 180.00 x 253.00
- Weight (g)
- 687
- 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, Frederick 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.
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