Efficient on-demand topology control for wireless ad hoc networks. - Yu Wang 003; Xinghua Shi (ICCCN, 2005)

The National Microbial Pathogen Database Resource (NMPDR): a genomics platform based on subsystem annotation. - Leslie Klis McNeil; Claudia Reich; Ramy K. Aziz; Daniela Bartels; Matthew Cohoon; Terry Disz; Robert A. Edwards; Svetlana Gerdes; Kaitlyn Hwang; Michael Kubal; Gohar Rem Margaryan; Folker Meyer; et al. (Nucleic Acids Res., 2007)

SWARM: a scientific workflow for supporting bayesian approaches to improve metabolic models. - Xinghua Shi; Rick Stevens (CLADE, 2008)

A Bayesian Approach to High-Throughput Biological Model Generation. - Xinghua Shi; Rick L. Stevens (BICoB, 2009)

Data Collection Capacity of Random-Deployed Wireless Sensor Networks. - Siyuan Chen 001; Yu Wang 003; Xiang-Yang Li 001; Xinghua Shi (GLOBECOM, 2009)

Enhanced Feature Selection and Generation for 802.11 User Identification. - Dingbang Xu; Yu Wang 003; Xinghua Shi (ICCCN, 2009)

Order-Optimal Data Collection in Wireless Sensor Networks: Delay and Capacity. - Siyuan Chen 001; Yu Wang 003; Xiang-Yang Li 001; Xinghua Shi (SECON, 2009)

Self-organizing fault-tolerant topology control in large-scale three-dimensional wireless networks. - Yu Wang 003; Lijuan Cao; Teresa A. Dahlberg; Fan Li 001; Xinghua Shi (ACM Trans. Auton. Adapt. Syst., 2009)

802.11 User Anonymization. - Dingbang Xu; Yu Wang 003; Xinghua Shi; Xiaohang Yin (GLOBECOM, 2010)

Convergence of General Nonstationary Iterative Methods for Solving Singular Linear Equations. - Xinghua Shi; Yimin Wei 001; Wen Zhang (SIAM J. Matrix Anal. Appl., 2011)

Capacity of data collection in randomly-deployed wireless sensor networks. - Siyuan Chen 001; Yu Wang 003; Xiang-Yang Li 001; Xinghua Shi (Wirel. Networks, 2011)

A sharp version of Bauer-Fike's theorem. - Xinghua Shi; Yimin Wei 001 (J. Comput. Appl. Math., 2012)

A Two-Graph Guided Multi-task Lasso Approach for eQTL Mapping. - Xiaohui Chen; Xinghua Shi; Xing Xu; Zhiyong Wang 005; Ryan Mills; Charles Lee; Jinbo Xu (AISTATS, 2012)

User identification and anonymization in 802.11 wireless LANs. - Dingbang Xu; Yu Wang 003; Xinghua Shi; Xiaohang Yin (Secur. Commun. Networks, 2012)

Using aggregate human genome data for individual identification. - Yue Wang 009; Xintao Wu; Xinghua Shi (BIBM, 2013)

A Survey of Social-Based Routing in Delay Tolerant Networks: Positive and Negative Social Effects. - Ying Zhu 011; Bin Xu 001; Xinghua Shi; Yu Wang 003 (IEEE Commun. Surv. Tutorials, 2013)

Unsupervised nonparametric anomaly detection: A kernel method. - Shaofeng Zou; Yingbin Liang; H. Vincent Poor; Xinghua Shi (Allerton, 2014)

CNVnet: combining sparse learning and biological networks to capture joint effect of copy number variants. - Zhiyong Wang 005; Jinbo Xu; Xinghua Shi (BCB, 2014)

Kernel-based nonparametric anomaly detection. - Shaofeng Zou; Yingbin Liang; H. Vincent Poor; Xinghua Shi (SPAWC, 2014)

Nonparametric Detection of Anomalous Data via Kernel Mean Embedding. - Shaofeng Zou; Yingbin Liang; H. Vincent Poor; Xinghua Shi (CoRR, 2014)

Finding Alternative Expression Quantitative Trait Loci by Exploring Sparse Model Space. - Zhiyong Wang 005; Jinbo Xu; Xinghua Shi (J. Comput. Biol., 2014)

Sequential parallel LASSO models for eQTL analysis. - Anhong He; Benika Hall; Jia Wen; Yingbin Liang; Xinghua Shi (BCB, 2015)

A Graph Community Approach for Constructing microRNA Networks. - Benika Hall; Andrew Quitadamo; Xinghua Shi (BigCom, 2015)

An integrated network of microRNA and gene expression in ovarian cancer. - Andrew Quitadamo; Lu Tian; Benika Hall; Xinghua Shi (BMC Bioinform., 2015)

A predictive model of gene expression using a deep learning framework. - Rui Xie; Andrew Quitadamo; Jianlin Cheng; Xinghua Shi (BIBM, 2016)

Building Bayesian networks from GWAS statistics based on Independence of Causal Influence. - Lu Zhang 021; Qiuping Pan; Xintao Wu; Xinghua Shi (BIBM, 2016)

Infringement of Individual Privacy via Mining Differentially Private GWAS Statistics. - Yue Wang 009; Jia Wen; Xintao Wu; Xinghua Shi (BigCom, 2016)

Bayesian Hyperparameter Optimization for Machine Learning Based eQTL Analysis. - Andrew Quitadamo; James Johnson; Xinghua Shi (BCB, 2017)

Lightweight Key Management for Group Communication in Body Area Networks through Physical Unclonable Functions. - Penglin Dong; Weichao Wang; Xinghua Shi; Tuanfa Qin (CHASE, 2017)

Lightweight mutual authentication among sensors in body area networks through Physical Unclonable Functions. - Liping Xie; Weichao Wang; Xinghua Shi; Tuanfa Qin (ICC, 2017)

A Sparse Learning Framework for Joint Effect Analysis of Copy Number Variants. - Zhiyong Wang 005; Benika Hall; Jinbo Xu; Xinghua Shi (IEEE ACM Trans. Comput. Biol. Bioinform., 2017)

Nonparametric Detection of Anomalous Data Streams. - Shaofeng Zou; Yingbin Liang; H. Vincent Poor; Xinghua Shi (IEEE Trans. Signal Process., 2017)

Using Deep Neural Network to Predict Drug Sensitivity of Cancer Cell Lines. - Yake Wang; Min Li 007; Ruiqing Zheng; Xinghua Shi; Yaohang Li; Fang-Xiang Wu; Jianxin Wang 001 (ICIC (2), 2018)

Participant Grouping for Privacy Preservation in Mobile Crowdsensing over Hierarchical Edge Clouds. - Ting Li 010; Zhijin Qiu; Lijuan Cao; Hanshang Li; Zhongwen Guo; Fan Li 001; Xinghua Shi; Yu Wang 003 (IPCCC, 2018)

Group spike-and-slab lasso generalized linear models for disease prediction and associated genes detection by incorporating pathway information. - Zaixiang Tang; Yueping Shen; Yan Li; Xinyan Zhang; Jia Wen; Chen'ao Qian; Wenzhuo Zhuang; Xinghua Shi; Nengjun Yi (Bioinform., 2018)

A Sparse Convolutional Predictor with Denoising Autoencoders for Phenotype Prediction. - Junjie Chen 004; Xinghua Shi (BCB, 2019)

A Survey on RFID Security and Privacy in Smart Medical: Threats and Protections. - Xinghua Shi; Jinxuan Cao; Tianliang Lu; Victor Chang 001 (IoTBDS, 2019)

Bayesian Network Construction and Genotype-Phenotype Inference Using GWAS Statistics. - Lu Zhang 021; Qiuping Pan; Yue Wang 009; Xintao Wu; Xinghua Shi (IEEE ACM Trans. Comput. Biol. Bioinform., 2019)

Population-scale Genomic Data Augmentation Based on Conditional Generative Adversarial Networks. - Junjie Chen 004; Mohammad Erfan Mowlaei; Xinghua Shi (BCB, 2020)

A parallelized strategy for epistasis analysis based on Empirical Bayesian Elastic Net models. - Jia Wen; Colby T. Ford; Daniel Janies; Xinghua Shi (Bioinform., 2020)

Accelerating bioinformatics research with International Conference on Intelligent Biology and Medicine 2020. - Yan Guo; Li Shen 001; Xinghua Shi; Kai Wang 063; Yulin Dai; Zhongming Zhao (BMC Bioinform., 2020)

Informatics and machine learning methods for health applications. - Li Shen 001; Xinghua Shi; Zhongming Zhao; Kai Wang 063 (BMC Medical Informatics Decis. Mak., 2020)

On the Convergence of Stochastic Compositional Gradient Descent Ascent Method. - Hongchang Gao; Xiaoqian Wang 001; Lei Luo; Xinghua Shi (IJCAI, 2021)

PAR-GAN: Improving the Generalization of Generative Adversarial Networks Against Membership Inference Attacks. - Junjie Chen 004; Wendy Hui Wang; Hongchang Gao; Xinghua Shi (KDD, 2021)

Differential Privacy Protection Against Membership Inference Attack on Machine Learning for Genomic Data. - Junjie Chen 004; Wendy Hui Wang; Xinghua Shi (PSB, 2021)

DeepDSC: A Deep Learning Method to Predict Drug Sensitivity of Cancer Cell Lines. - Min Li 007; Yake Wang; Ruiqing Zheng; Xinghua Shi; Yaohang Li; Fang-Xiang Wu; Jianxin Wang 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

Privacy-Preserving Participant Grouping for Mobile Social Sensing Over Edge Clouds. - Ting Li 010; Zhijin Qiu; Lijuan Cao; Dazhao Cheng; Weichao Wang; Xinghua Shi; Yu Wang 003 (IEEE Trans. Netw. Sci. Eng., 2021)

Offspring GAN augments biased human genomic data. - Supratim Das; Xinghua Shi (BCB, 2022)

Participant Selection for Hierarchical Federated Learning in Edge Clouds. - Xinliang Wei; Jiyao Liu; Xinghua Shi; Yu Wang 003 (NAS, 2022)

An autoencoder-based deep learning method for genotype imputation. - Meng Song; Jonathan Greenbaum; Joseph Luttrell IV; Weihua Zhou; Chong Wu; Zhe Luo; Chuan Qiu; Lan Juan Zhao; Kuan-Jui Su; Qing Tian 004; Hui Shen 007; Huixiao Hong; et al. (Frontiers Artif. Intell., 2022)

FedDP: Secure Federated Learning with Differential Privacy for Disease Prediction. - Bin Li; Hongchang Gao; Xinghua Shi (ICCABS, 2023)

Multi-Energy Coordinated Day-ahead Energy Management of Integrated Electrical-Gas Energy System. - Xinghua Shi; Jia Feng; Fan Zhang; Chuangxin Guo (IoTAAI, 2023)

Can Decentralized Stochastic Minimax Optimization Algorithms Converge Linearly for Finite-Sum Nonconvex-Nonconcave Problems? - Yihan Zhang; Wenhao Jiang; Feng Zheng; Chiu C. Tan 001; Xinghua Shi; Hongchang Gao (CoRR, 2023)

Discriminative Forests Improve Generative Diversity for Generative Adversarial Networks. - Junjie Chen 004; Jiahao Li; Chen Song; Bin Li; Qingcai Chen; Hongchang Gao; Wendy Hui Wang; Zenglin Xu; Xinghua Shi (AAAI, 2024)

SparseHE: An Efficient Privacy-Preserving Biomedical Prediction Approach Using Sparse Homomorphic Encryption. - Chen Song; Wenkang Zhan; Xinghua Shi (ICHI, 2024)

Identification of Parkinson's disease PACE subtypes and repurposing treatments through integrative analyses of multimodal data. - Chang Su 002; Yu Hou; Jielin Xu; Zhenxing Xu; Manqi Zhou; Alison Ke; Haoyang Li 001; Jie Xu 012; Matthew Brendel; Jacqueline R. M. A. Maasch; Zilong Bai; Haotan Zhang; et al. (npj Digit. Medicine, 2024)

Joint Participant and Learning Topology Selection for Federated Learning in Edge Clouds. - Xinliang Wei; Kejiang Ye; Xinghua Shi; Cheng-Zhong Xu 001; Yu Wang 003 (IEEE Trans. Parallel Distributed Syst., 2024)

FSLearning: An Efficient Federated Split Learning Framework for Privacy-Preserving Disease Prediction. - Bin Li; Xiaoqian Jiang; Yu-Chun Hsu; Arif Ozgun Harmanci; Hongchang Gao; Xinghua Shi (AIME (1), 2025)

DKGM: A diffusion knowledge graph model for medication recommendation leveraging medical and drug information. - Yang Zhao; Pei Wang; Xinghua Shi (ICHI, 2025)