Random regression models for the prediction of days to weight, ultrasound rib eye area, and ultrasound back fat depth in beef cattle

2016 ◽  
Vol 94 (2) ◽  
pp. 471-482 ◽  
Author(s):  
S. E. Speidel ◽  
R. K. Peel ◽  
D. H. Crews ◽  
R. M. Enns
Keyword(s):  
Beef Cattle ◽  
Regression Models ◽  
Random Regression

scholarly journals Genetic evaluation using multi-trait and random regression models in Simmental beef cattle

2013 ◽  
Vol 12 (3) ◽  
pp. 2465-2480 ◽  
Author(s):  
R.R. Mota ◽  
L.F.A. Marques ◽  
P.S. Lopes ◽  
L.P. da Silva ◽  
F.R.A. Neto ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Regression Models ◽  
Genetic Evaluation ◽  
Random Regression

scholarly journals APPLICATION OF RANDOM REGRESSION MODELS FOR GROWTH TRAITS OF NELLORE CATTLE IN BRAZIL

2016 ◽  
Vol 8 (2) ◽  
pp. 45-54
Author(s):  
Wéverton José Lima Fonseca ◽  
Amauri Felipe Evangelista ◽  
Laylson Da Silva Borges ◽  
Gleissa Mayone Silva Vogado ◽  
Carlos Syllas Monteiro Luz ◽  
...  
Keyword(s):  
Longitudinal Data ◽  
Beef Cattle ◽  
Regression Models ◽  
Growth Traits ◽  
Standard Procedure ◽  
Random Regression ◽  
Nellore Cattle ◽  
Cattle Breeders ◽  
Estimate Variance ◽  
Genetic Evaluations

The purpose of this review is to show the increase in number of researches on covariance components and genetic evaluation using random regression models (RRM) for growth traits of Nellore cattle. Random regression models, also known as infinite-dimension models have been used to estimate variance components and genetic parameters for weight of beef cattle. In addition, those models are a standard alternative for genetic analyses of longitudinal data, however, the availibility of computational resources for performing genetic evaluations widely is an obstacle. Traits related to animal growth are adopted as selection criteria in beef cattle breeding programs, because the remuneration of cattle breeders is made based on the weight of carcasses. In recent years, RRM have been adopted as standard procedure in relation to the analysis of longitudinal data in animal breeding.

scholarly journals Influence of animals obtained using embryo transfer on the genetic evaluation of growth in Simmental beef cattle with random regression models

2013 ◽  
Vol 12 (4) ◽  
pp. 5889-5904
Author(s):  
R.R. Mota ◽  
P.S. Lopes ◽  
L.F.A. Marques ◽  
L.P. Silva ◽  
M. Conceição Pessoa ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Embryo Transfer ◽  
Regression Models ◽  
Genetic Evaluation ◽  
Random Regression

scholarly journals Random regression models in the evaluation of the growth curve of Simbrasil beef cattle

2013 ◽  
Vol 12 (1) ◽  
pp. 528-536 ◽  
Author(s):  
R.R. Mota ◽  
L.F.A. Marques ◽  
P.S. Lopes ◽  
L.P. da Silva ◽  
A.M. Hidalgo ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Growth Curve ◽  
Regression Models ◽  
Random Regression

scholarly journals MicroRNA profiles of dry secretions through the first three weeks of the dry period from Holstein cows

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ellie J. Putz ◽  
Austin M. Putz ◽  
Hyeongseon Jeon ◽  
John D. Lippolis ◽  
Hao Ma ◽  
...  
Keyword(s):  
Regression Models ◽  
Transition Period ◽  
Mirna Profile ◽  
Random Regression ◽  
Q Value ◽  
Dry Period ◽  
Regulate Gene Expression ◽  
Intramammary Infections ◽  
Non Coding Rnas ◽  
Insight Into

AbstractIn dairy cows, the period from the end of lactation through the dry period and into the transition period, requires vast physiological and immunological changes critical to mammary health. The dry period is important to the success of the next lactation and intramammary infections during the dry period will adversely alter mammary function, health and milk production for the subsequent lactation. MicroRNAs (miRNAs) are small non-coding RNAs that can post transcriptionally regulate gene expression. We sought to characterize the miRNA profile in dry secretions from the last day of lactation to 3, 10, and 21 days post dry-off. We identified 816 known and 80 novel miRNAs. We found 46 miRNAs whose expression significantly changed (q-value < 0.05) over the first three weeks of dry-off. Additionally, we examined the slopes of random regression models of log transformed normalized counts and cross analyzed the 46 significantly upregulated and downregulated miRNAs. These miRNAs were found to be associated with important components of pregnancy, lactation, as well as inflammation and disease. Detailing the miRNA profile of dry secretions through the dry-off period provides insight into the biology at work, possible means of regulation, components of resistance and/or susceptibility, and outlets for targeted therapy development.

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