A haplotype-based framework for group-wise transmission/disequilibrium tests for rare variant association analysis. - Rui Chen 021; Qiang Wei; Xiaowei Zhan; Xue Zhong; James S. Sutcliffe; Nancy J. Cox; Edwin H. Cook Jr.; Chun Li; Wei Chen 074; Bingshan Li (Bioinform., 2015)

De novo pattern discovery enables robust assessment of functional consequences of non-coding variants. - Hai Yang 002; Rui Chen 021; Quan Wang 004; Qiang Wei; Ying Ji 002; Guangze Zheng 002; Xue Zhong; Nancy J. Cox; Bingshan Li (Bioinform., 2019)

DRAMS: A tool to detect and re-align mixed-up samples for integrative studies of multi-omics data. - Yi Jiang; Gina Giase; Kay Grennan; Annie W. Shieh; Yan Xia; Lide Han; Quan Wang 004; Qiang Wei; Rui Chen 021; Sihan Liu; Kevin P. White; Chao Chen 041; et al. (PLoS Comput. Biol., 2020)

Subtype-GAN: a deep learning approach for integrative cancer subtyping of multi-omics data. - Hai Yang 002; Rui Chen 021; Dongdong Li; Zhe Wang 002 (Bioinform., 2021)

A Bayesian framework to integrate multi-level genome-scale data for Autism risk gene prioritization. - Ying Ji 002; Rui Chen 021; Quan Wang 004; Qiang Wei; Ran Tao; Bingshan Li (BMC Bioinform., 2022)

TVAR: assessing tissue-specific functional effects of non-coding variants with deep learning. - Hai Yang 002; Rui Chen 021; Quan Wang 004; Qiang Wei; Ying Ji 002; Xue Zhong; Bingshan Li (Bioinform., 2022)

From multi-omics data to the cancer druggable gene discovery: a novel machine learning-based approach. - Hai Yang 002; Lipeng Gan; Rui Chen 021; Dongdong Li; Jing Zhang 041; Zhe Wang 002 (Briefings Bioinform., 2023)

Improving Genetic Perturbation Response Prediction with an Enhanced Biological Knowledge Graph. - Yang Li; Rui Chen 021; Yuting Tan 005; Xue Zhong; Bingshan Li; Zhijun Yin (BIBM, 2024)