A sequence-based method to predict the impact of regulatory variants using random forest. - Qiao Liu 008; Mingxin Gan; Rui Jiang 001 (BMC Syst. Biol., 2017)

Chromatin accessibility prediction via a hybrid deep convolutional neural network. - Qiao Liu 008; Fei Xia 002; Qijin Yin; Rui Jiang 001 (Bioinform., 2018)

Automatically Structuring on Chinese Ultrasound Report of Cerebrovascular Diseases via Natural Language Processing. - Pengyu Chen; Qiao Liu 008; Lan Wei; Beier Zhao; Yin Jia; Hairong Lv; Xiaolu Fei (IEEE Access, 2019)

hicGAN infers super resolution Hi-C data with generative adversarial networks. - Qiao Liu 008; Hairong Lv; Rui Jiang 001 (Bioinform., 2019)

DeepHistone: a deep learning approach to predicting histone modifications. - Qijin Yin; Mengmeng Wu; Qiao Liu 008; Hairong Lv; Rui Jiang 001 (BMC Genom., 2019)

EpiFIT: functional interpretation of transcription factors based on combination of sequence and epigenetic information. - Shaoming Song; Hongfei Cui; Shengquan Chen; Qiao Liu 008; Rui Jiang 001 (Quant. Biol., 2019)

Feature-Enhanced Graph Networks for Genetic Mutational Prediction Using Histopathological Images in Colon Cancer. - Kexin Ding; Qiao Liu 008; Edward Lee; Mu Zhou; Aidong Lu; Shaoting Zhang 001 (MICCAI (2), 2020)

Reinforced Molecular Optimization with Neighborhood-Controlled Grammars. - Chencheng Xu; Qiao Liu 008; Minlie Huang; Tao Jiang 001 (NeurIPS, 2020)

DeepCDR: a hybrid graph convolutional network for predicting cancer drug response. - Qiao Liu 008; Zhiqiang Hu; Rui Jiang 001; Mu Zhou (Bioinform., 2020)

Quantifying functional impact of non-coding variants with multi-task Bayesian neural network. - Chencheng Xu; Qiao Liu 008; Jianyu Zhou; Minzhu Xie; Jianxing Feng; Tao Jiang 001 (Bioinform., 2020)

Roundtrip: A Deep Generative Neural Density Estimator. - Qiao Liu 008; Jiaze Xu; Rui Jiang 001; Wing Hung Wong (CoRR, 2020)

Multimodal single cell data integration challenge: Results and lessons learned. - Christopher Lance; Malte D. Lücken; Daniel B. Burkhardt; Robrecht Cannoodt; Pia Rautenstrauch; Anna Laddach; Aidyn Ubingazhibov; Zhi-Jie Cao; Kaiwen Deng; Sumeer Khan; Qiao Liu 008; Nikolay Russkikh; et al. (NeurIPS (Competition and Demos), 2021)

Boost Neural Networks by Checkpoints. - Feng Wang 047; Guoyizhe Wei; Qiao Liu 008; Jinxiang Ou; Xian Wei; Hairong Lv (NeurIPS, 2021)

OpenAnnotate: a web server to annotate the chromatin accessibility of genomic regions. - Shengquan Chen; Qiao Liu 008; Xuejian Cui; Zhan-Ying Feng; Chunquan Li; Xiaowo Wang; Xuegong Zhang; Yong Wang; Rui Jiang 001 (Nucleic Acids Res., 2021)

Simultaneous deep generative modelling and clustering of single-cell genomic data. - Qiao Liu 008; Shengquan Chen; Rui Jiang 001; Wing Hung Wong (Nat. Mach. Intell., 2021)

scGraph: a graph neural network-based approach to automatically identify cell types. - Qijin Yin; Qiao Liu 008; Zhuoran Fu; Wanwen Zeng; Boheng Zhang; Xuegong Zhang; Rui Jiang 001; Hairong Lv (Bioinform., 2022)

DualGCN: a dual graph convolutional network model to predict cancer drug response. - Tianxing Ma; Qiao Liu 008; Haochen Li 003; Mu Zhou; Rui Jiang 001; Xuegong Zhang (BMC Bioinform., 2022)

Graph Convolutional Networks for Multi-modality Medical Imaging: Methods, Architectures, and Clinical Applications. - Kexin Ding; Mu Zhou; Zichen Wang; Qiao Liu 008; Corey W. Arnold; Shaoting Zhang 001; Dimitris N. Metaxas (CoRR, 2022)

Mutual Information Learned Classifiers: an Information-theoretic Viewpoint of Training Deep Learning Classification Systems. - Jirong Yi; Qiaosheng Zhang; Zhen Chen; Qiao Liu 008; Wei Shao (CoRR, 2022)

Mutual Information Learned Regressor: an Information-theoretic Viewpoint of Training Regression Systems. - Jirong Yi; Qiaosheng Zhang; Zhen Chen; Qiao Liu 008; Wei Shao; Yusen He; Yaohua Wang (CoRR, 2022)

CausalEGM: a general causal inference framework by encoding generative modeling. - Qiao Liu 008; Zhongren Chen; Wing Hung Wong (CoRR, 2022)

DeepCAGE: Incorporating Transcription Factors in Genome-wide Prediction of Chromatin Accessibility. - Qiao Liu 008; Kui Hua; Xuegong Zhang; Wing Hung Wong; Rui Jiang 001 (Genom. Proteom. Bioinform., 2022)

AggEnhance: Aggregation Enhancement by Class Interior Points in Federated Learning with Non-IID Data. - Jinxiang Ou; Yunheng Shen; Feng Wang 047; Qiao Liu 008; Xuegong Zhang; Hairong Lv (ACM Trans. Intell. Syst. Technol., 2022)

Deep generative modeling and clustering of single cell Hi-C data. - Qiao Liu 008; Wanwen Zeng; Wei Zhang 241; Sicheng Wang; Hongyang Chen; Rui Jiang 001; Mu Zhou; Shaoting Zhang 001 (Briefings Bioinform., 2023)

HiChIPdb: a comprehensive database of HiChIP regulatory interactions. - Wanwen Zeng; Qiao Liu 008; Qijin Yin; Rui Jiang 001; Wing Hung Wong (Nucleic Acids Res., 2023)

DeepDrug: A general graph-based deep learning framework for drug-drug interactions and drug-target interactions prediction. - Qijin Yin; Rui Fan; Xusheng Cao; Qiao Liu 008; Rui Jiang 001; Wanwen Zeng (Quant. Biol., 2023)

Inferring Gene Regulatory Network Based on scATAC-seq Data with Gene Perturbation. - Wei Shao; Yuti Liu; Shuang Zhang; Shuang Chen; Qiao Liu 008; Jianyu Zhou; Wanwen Zeng (BIBM, 2024)

Sampling-guided Heterogeneous Graph Neural Network with Temporal Smoothing for Scalable Longitudinal Data Imputation. - Zhaoyang Zhang; Ziqi Chen; Qiao Liu 008; Jinhan Xie; Hongtu Zhu (CoRR, 2024)

DeepAEG: a model for predicting cancer drug response based on data enhancement and edge-collaborative update strategies. - Chuanqi Lao; Pengfei Zheng; Hongyang Chen; Qiao Liu 008; Feng An; Zhao Li 007 (BMC Bioinform., 2024)

Deconer: An Evaluation Toolkit for Reference-based Deconvolution Methods Using Gene Expression Data. - Wei Zhang 241; Xianglin Zhang; Qiao Liu 008; Lei Wei; Xu Qiao; Rui Gao 006; Zhiping Liu; Xiaowo Wang (Genom. Proteom. Bioinform., 2025)

An AI-powered Bayesian generative modeling approach for causal inference in observational studies. - Qiao Liu 008; Wing Hung Wong (CoRR, 2025)