This document introduces Shiny apps and R packages for animal science created by Youngjun Na. It describes the adatalab project which contains packages for analyzing animal nutrition data and modeling. These include packages for dairy cattle, beef cattle, goats, and feeding information. It also introduces two Shiny apps, DairyLab and HanwooLab, for processing, visualizing and modeling dairy and beef cattle performance and productivity data. The apps are deployed on Github pages through embedding an iframe.
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Shiny for animal science
1. Shiny for animal science:
project adatalab
Youngjun Na, PhD
Department of animal science and technology
Konkuk University
Email: ruminoreticulum@gmail.com
2. library(youngjunna)
# Information ----
Name <- ”Youngjun Na”
Family <- data.frame(
family = c(“wife”, “son”, “daughter”),
name = c(“Juhee”, “Sangwoo”, “Haon”)
)
# Link ----
[Github](“https://github.com/YoungjunNa”)
[TechnicalBlog](“https://youngjunna.github.io”)
13. Package: CH4goat
§ https://github.com/adatalab/CH4goat
§ Imports: neuralnet
§ The package contains two black-box model derived from the in vivo enteric
methane dataset using respiration-metabolism chamber system.
§ neuralnet::compute(model1, your_data)