29 citations · 77 across the 13 of their papers we have counts for
14 papers
A U-Statistic-based random forest approach for genetic interaction study
Ming Li, Ruo-Sin Peng, Changshuai Wei +1
Variations in complex traits are influenced by multiple genetic variants, environmental risk factors, and their interactions. Though substantial progress has been made in identifyi…
Collapsing ROC approach for risk prediction research on both common and rare variants
Changshuai Wei, Qing Lu
Risk prediction that capitalizes on emerging genetic findings holds great promise for improving public health and clinical care. However, recent risk prediction research has shown…
Functional Analysis of Variance for Association Studies
Olga A. Vsevolozhskaya, Dmitri V. Zaykin, Mark C. Greenwood +2
While progress has been made in identifying common genetic variants associated with human diseases, for most of common complex diseases, the identified genetic variants only accoun…
A multi-locus predictiveness curve and its summary assessment for genetic risk prediction
Changshuai Wei, Ming Li, Yalu Wen +2
With the advance of high-throughput genotyping and sequencing technologies, it becomes feasible to comprehensive evaluate the role of massive genetic predictors in disease predicti…
A Kernel-Based Neural Network for High-dimensional Genetic Risk Prediction Analysis
Xiaoxi Shen, Xiaoran Tong, Qing Lu
Risk prediction capitalizing on emerging human genome findings holds great promise for new prediction and prevention strategies. While the large amounts of genetic data generated f…
Asymptotic Theory of Expectile Neural Networks
Jinghang Lin, Xiaoxi Shen, Qing Lu
Neural networks are becoming an increasingly important tool in applications. However, neural networks are not widely used in statistical genetics. In this paper, we propose a new n…