標(biāo)題: Titlebook: Genetic Data Analysis for Plant and Animal Breeding; Fikret Isik,James Holland,Christian Maltecca Book 2017 Springer International Publish [打印本頁(yè)] 作者: 削木頭 時(shí)間: 2025-3-21 19:46
書目名稱Genetic Data Analysis for Plant and Animal Breeding影響因子(影響力)
書目名稱Genetic Data Analysis for Plant and Animal Breeding影響因子(影響力)學(xué)科排名
書目名稱Genetic Data Analysis for Plant and Animal Breeding網(wǎng)絡(luò)公開(kāi)度
書目名稱Genetic Data Analysis for Plant and Animal Breeding網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書目名稱Genetic Data Analysis for Plant and Animal Breeding被引頻次
書目名稱Genetic Data Analysis for Plant and Animal Breeding被引頻次學(xué)科排名
書目名稱Genetic Data Analysis for Plant and Animal Breeding年度引用
書目名稱Genetic Data Analysis for Plant and Animal Breeding年度引用學(xué)科排名
書目名稱Genetic Data Analysis for Plant and Animal Breeding讀者反饋
書目名稱Genetic Data Analysis for Plant and Animal Breeding讀者反饋學(xué)科排名
作者: Robust 時(shí)間: 2025-3-21 20:48 作者: Abrupt 時(shí)間: 2025-3-22 03:56
Tapan K. Sengupta,Swagata Bhaumik familiar with traditional analysis of variance (ANOVA) based on ordinary least squares methods, we first will review the ANOVA and compare ANOVA to mixed models analysis to help introduce this topic. We will show that under certain conditions, results from ANOVA and mixed models analysis are largel作者: 細(xì)胞學(xué) 時(shí)間: 2025-3-22 07:31
DOGMA 2003. Report from Denmarkn particular, ASReml makes use of a notation for direct products of matrices to form some complex variance structures. The direct product notation can be applied both to the residual errors from the model (in the ‘. structure’) and to random model factors (in the ‘. structure’). In this chapter we i作者: 大量 時(shí)間: 2025-3-22 09:23 作者: Limpid 時(shí)間: 2025-3-22 16:52 作者: Limpid 時(shí)間: 2025-3-22 20:32
,Befehle der Befehls-Oberfl?che,n plant and animal breeding programs. When traits are correlated, breeding value predictions from a multivariate model can be more accurate than univariate models. In this chapter we introduce multivariate models for two data sets: a maize inbred line multi-environment trial and pig data with pedigr作者: 原始 時(shí)間: 2025-3-22 23:48 作者: 微枝末節(jié) 時(shí)間: 2025-3-23 03:53
https://doi.org/10.1007/978-3-8349-6242-3onmental conditions to which a cultivar might be exposed. Multi-environment trials provide information about the adaptability of genotypes to specific environments or to sets of environments. The variance-covariance structures introduced in preceding chapters can be used to model genotype-by-environ作者: myalgia 時(shí)間: 2025-3-23 09:00 作者: Perineum 時(shí)間: 2025-3-23 11:24 作者: Rustproof 時(shí)間: 2025-3-23 17:25 作者: 長(zhǎng)矛 時(shí)間: 2025-3-23 21:28 作者: Canopy 時(shí)間: 2025-3-23 23:26 作者: 一再煩擾 時(shí)間: 2025-3-24 06:19 作者: 土產(chǎn) 時(shí)間: 2025-3-24 09:26
,Befehle der Befehls-Oberfl?che,n plant and animal breeding programs. When traits are correlated, breeding value predictions from a multivariate model can be more accurate than univariate models. In this chapter we introduce multivariate models for two data sets: a maize inbred line multi-environment trial and pig data with pedigree information appropriate for an animal model.作者: institute 時(shí)間: 2025-3-24 10:42
DRM, a Design Research Methodology missing genotype values. The chapter is not intended as a rigorous treatment of the use and implications of imputation in breeding values prediction, but rather as a brief overview of some common strategies currently employed. For the reader interested in a more in-depth treatment, references are provided within the chapter.作者: 錢財(cái) 時(shí)間: 2025-3-24 15:30 作者: 潰爛 時(shí)間: 2025-3-24 20:14
Breeding Values,‘a(chǎn)nimal’ model is introduced to demonstrate prediction of individual breeding values across generations. Modifications to the basic model are considered, such as maternal effects and genetic group effects.作者: 我正派 時(shí)間: 2025-3-25 02:26 作者: 高原 時(shí)間: 2025-3-25 05:21 作者: 非秘密 時(shí)間: 2025-3-25 09:18 作者: DAMN 時(shí)間: 2025-3-25 12:33
Fikret Isik,James Holland,Christian MalteccaStep-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作者: 起草 時(shí)間: 2025-3-25 19:38 作者: incarcerate 時(shí)間: 2025-3-25 21:44 作者: DEVIL 時(shí)間: 2025-3-26 03:55 作者: 指令 時(shí)間: 2025-3-26 05:56
Multi Environmental Trials,environments to more parsimonious models, such as factor analytic structures, which require fewer parameters. Factor analytical structures can often efficiently capture the genotype-by-environment patterns without requiring extraordinary model complexity.作者: 煩憂 時(shí)間: 2025-3-26 11:09
ms 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 978-3-319-85586-8978-3-319-55177-7作者: PACK 時(shí)間: 2025-3-26 13:17 作者: 不幸的人 時(shí)間: 2025-3-26 18:47 作者: 螢火蟲 時(shí)間: 2025-3-26 23:16 作者: 執(zhí)拗 時(shí)間: 2025-3-27 03:01
Introduction to ASReml Software,tware very fast to solve large number of mixed model equations. The software is flexible to fit complex variance structures in mixed models. We introduce ASReml stand alone and a brief introduction to ASReml-R in this chapter. Fitting more complex variance structures in mixed models using ASReml is 作者: 蒸發(fā) 時(shí)間: 2025-3-27 07:35 作者: 古董 時(shí)間: 2025-3-27 10:50
Variance Modeling in ASReml,n particular, ASReml makes use of a notation for direct products of matrices to form some complex variance structures. The direct product notation can be applied both to the residual errors from the model (in the ‘. structure’) and to random model factors (in the ‘. structure’). In this chapter we i作者: LUT 時(shí)間: 2025-3-27 15:04
Breeding Values,‘a(chǎn)nimal’ model is introduced to demonstrate prediction of individual breeding values across generations. Modifications to the basic model are considered, such as maternal effects and genetic group effects.作者: 荒唐 時(shí)間: 2025-3-27 20:11 作者: obstinate 時(shí)間: 2025-3-28 00:35 作者: sorbitol 時(shí)間: 2025-3-28 04:55 作者: facilitate 時(shí)間: 2025-3-28 09:08
Multi Environmental Trials,onmental conditions to which a cultivar might be exposed. Multi-environment trials provide information about the adaptability of genotypes to specific environments or to sets of environments. The variance-covariance structures introduced in preceding chapters can be used to model genotype-by-environ作者: 糾纏,纏繞 時(shí)間: 2025-3-28 13:50 作者: visceral-fat 時(shí)間: 2025-3-28 18:08
Imputing Missing Genotypes, missing genotype values. The chapter is not intended as a rigorous treatment of the use and implications of imputation in breeding values prediction, but rather as a brief overview of some common strategies currently employed. For the reader interested in a more in-depth treatment, references are p作者: 魔鬼在游行 時(shí)間: 2025-3-28 22:12
Genomic Relationships and GBLUP, the use of large numbers of DNA markers to estimate the amount of genome shared by individuals. Genetic similarity estimates based on genetic markers are more precise than those based on pedigree information. Using the genomic relationships derived from markers for prediction of genetic merit of in作者: PET-scan 時(shí)間: 2025-3-29 02:57 作者: Dappled 時(shí)間: 2025-3-29 04:11 作者: Psa617 時(shí)間: 2025-3-29 10:56
DOGMA 2003. Report from Denmark be applied both to the residual errors from the model (in the ‘. structure’) and to random model factors (in the ‘. structure’). In this chapter we introduce the major variance models to form more complex . and . structures with some examples, but more detailed applications of variance modeling will be covered in later chapters.作者: Monotonous 時(shí)間: 2025-3-29 13:32 作者: acrimony 時(shí)間: 2025-3-29 16:27 作者: Lime石灰 時(shí)間: 2025-3-29 20:06
Book 2017ontext 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 progr作者: FLING 時(shí)間: 2025-3-30 02:46 作者: thalamus 時(shí)間: 2025-3-30 05:57
