Shihong Mao

2017

A researcher in the Science corpus: 1 paper; trusts 0 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Papers from Shihong Mao's perspective

Ordered by how strongly the researchers Shihong Mao trusts endorse each paper. Same corpus, a different order for every researcher.

1. Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores
2. Boosting: Foundations and Algorithms
3. The Elements of Statistical Learning
4. Common SNPs explain a large proportion of heritability for human height (Nature Genetics)
5. Accuracy of Predicting the Genetic Risk of Disease Using a Genome-Wide Approach (PLoS ONE)
6. Improving accuracy of genomic predictions within and between dairy cattle breeds with imputed high-density single nucleotide polymorphism panels. (Journal of Dairy Science)
7. Pitfalls of predicting complex traits from SNPs
8. Genomic selection: prediction of accuracy and maximisation of long term response (Genetica)
9. Regression Shrinkage and Selection via the Lasso
10. Estimating Effects and Making Predictions from Genome-Wide Marker Data

Their papers

• A machine-learning heuristic to improve gene score prediction of polygenic traits (2017) — 82 citations