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Article summary:
1. HIBLUP is a new integration of statistical models on the BLUP framework for efficient genetic evaluation using big genomic data.
2. HIBLUP can improve the accuracy and efficiency of genetic evaluation by combining multiple statistical models into one unified model.
3. The authors tested HIBLUP on two real datasets and found that it was able to accurately predict the breeding values with high accuracy and efficiency.
Article analysis:
The article is generally reliable and trustworthy, as it provides evidence from two real datasets to support its claims about the effectiveness of HIBLUP in improving the accuracy and efficiency of genetic evaluation. The authors also provide detailed descriptions of their methodology, which allows readers to understand how they arrived at their conclusions. Furthermore, the article does not appear to be biased or one-sided, as it presents both sides of the argument equally and does not make any unsupported claims or omit any points of consideration. Additionally, there are no promotional elements in the article, nor does it present any partiality towards either side of the argument. Finally, possible risks are noted throughout the article, making it clear that further research is needed before HIBLUP can be used in practice.