8 citations · 10 across the 4 of their papers we have counts for
5 papers
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…
Expectile Neural Networks for Genetic Data Analysis of Complex Diseases
Jinghang Lin, Xiaoran Tong, Chenxi Li +1
The genetic etiologies of common diseases are highly complex and heterogeneous. Classic statistical methods, such as linear regression, have successfully identified numerous geneti…
Asymptotic Properties of Neural Network Sieve Estimators
Xiaoxi Shen, Chang Jiang, Lyudmila Sakhanenko +1
Neural networks are one of the most popularly used methods in machine learning and artificial intelligence nowadays. Due to the universal approximation theorem (Hornik et al. (1989…
GWGGI: software for genome-wide gene-gene interaction analysis
Changshuai Wei, Qing Lu
Background: While the importance of gene-gene interactions in human diseases has been well recognized, identifying them has been a great challenge, especially through association s…