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Genetic Association Studies: Background, Conduct, Analysis, Interpretation

Autor Mehmet Tevfik Dorak
en Limba Engleză Paperback – 26 sep 2016
Genetic Association Studies is designed for students of public health, epidemiology, and the health sciences, covering the main principles of molecular genetics, population genetics, medical genetics, epidemiology and statistics. It presents a balanced view of genetic associations with coverage of candidate gene studies as well as genome-wide association studies. All aspects of a genetic association study are included, from the lab to analysis and interpretation of results, but also bioinformatics approaches to causality assessment. The role of the environment in genetic disease is also highlighted. Genetic Association Studies will enable readers to understand and critique genetic association studies and set them on the way to designing, executing, analyzing, interpreting, and reporting their own.
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Specificații

ISBN-13: 9780815344636
ISBN-10: 0815344635
Pagini: 240
Ilustrații: 75
Dimensiuni: 174 x 246 x 15 mm
Greutate: 0.41 kg
Ediția:1
Editura: CRC Press
Colecția Garland Science

Public țintă

Postgraduate

Cuprins

1. Primer on Molecular Genetics  2. Primer on Medical Genetics  3. Primer on Population Genetics  4. Epidemiologic Principles and Genetic Association Studies  5. Environmental Epidemiology in the Context of Genetic Epidemiology  6. Elementary Statistical Concepts  7. Genotyping Methods and Errors  8. Candidate Gene Studies and Genome-Wide Association Studies  9. Statistical Analysis of Genetic Association Study Results  10. Bioinformatics for the Interpretation of Genetic Association Study Results  11. Genetic Risk Profiling and Medical Applications of Genetic Associations

Descriere

Genetic Association Studies is designed for students of public health, epidemiology, and the health sciences who need a non-mathematical introduction to genetic epidemiology. It provides a multi-faceted approach to genetic association studies covering molecular genetics, epidemiology, and statistics as a foundation for genetic associations. Both candidate gene and genome-wide studies are included as well as bioinformatics approaches to the interpretation of results.