| 书目名称 | Genetic Data Analysis for Plant and Animal Breeding |
| 编辑 | Fikret Isik,James Holland,Christian Maltecca |
| 视频video | |
| 概述 | Step-by-step data analysis examples for readers to learn quickly and apply in their own research.The first ‘how to‘ book on analyzing genomic data for plant and animal breeding.Fills the gap between t |
| 图书封面 |  |
| 描述 | This book fills the gap between textbooks of quantitative genetic theory, and software manuals that provide details on analytical methods but little context or perspective on which methods may be most appropriate for a particular application. Accordingly this book is composed of two sections. The first section (Chapters 1 to 8) covers topics of classical phenotypic data analysis for prediction of breeding values in animal and plant breeding programs. In the second section (Chapters 9 to 13) we provide the concept and overall review of available tools for using DNA markers for predictions of genetic merits in breeding populations. With advances in DNA sequencing technologies, genomic data, especially single nucleotide polymorphism (SNP) markers, have become available for animal and plant breeding programs in recent years. Analysis of DNA markers for prediction of genetic merit is a relatively new and active research area. The algorithms and software to implement these algorithms are changing rapidly. This section represents state-of-the-art knowledge on the tools and technologies available for genetic analysis of plants and animals. However, readers should be aware that the methods |
| 出版日期 | Book 2017 |
| 关键词 | Associate genetics; Genomic selection; Mixed models; Plant and animal breeding; Quantitative genetics |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-55177-7 |
| isbn_softcover | 978-3-319-85586-8 |
| isbn_ebook | 978-3-319-55177-7 |
| copyright | Springer International Publishing AG 2017 |
发表于 2025-3-21 19:46:36
