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Item Details
| Title:
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THE FUNDAMENTALS OF MODERN STATISTICAL GENETICS
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| By: |
Nan M. Laird, Christoph Lange |
| Format: |
Hardback |
| List price:
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£74.99 |
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We currently do not stock this item, please contact the publisher directly for
further information.
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| ISBN 10: |
1441973370 |
| ISBN 13: |
9781441973375 |
| Publisher: |
SPRINGER-VERLAG NEW YORK INC. |
| Pub. date: |
2 December, 2010 |
| Series: |
Statistics for Biology and Health |
| Pages: |
226 |
| Description: |
This book offers statistical models and methods used to understand human genetics, focusing on modern approaches to association analysis. Numerous examples illustrate key points, and the text includes exercises for students with a broad range of skill levels. |
| Synopsis: |
This book covers the statistical models and methods that are used to understand human genetics, following the historical and recent developments of human genetics. Starting with Mendel's first experiments to genome-wide association studies, the book describes how genetic information can be incorporated into statistical models to discover disease genes. All commonly used approaches in statistical genetics (e.g. aggregation analysis, segregation, linkage analysis, etc), are used, but the focus of the book is modern approaches to association analysis. Numerous examples illustrate key points throughout the text, both of Mendelian and complex genetic disorders.The intended audience is statisticians, biostatisticians, epidemiologists and quantitatively- oriented geneticists and health scientists wanting to learn about statistical methods for genetic analysis, whether to better analyze genetic data, or to pursue research in methodology. A background in intermediate level statistical methods is required. The authors include few mathematical derivations, and the exercises provide problems for students with a broad range of skill levels. No background in genetics is assumed. |
| Illustrations: |
XIV, 226 p. |
| Publication: |
US |
| Imprint: |
Springer-Verlag New York Inc. |
| Returns: |
Returnable |
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