Publications

Highlighted papers

(For a full list see below or go to Google Scholar)

Density estimation using deep generative neural networks

We introduce a new general-purpose density estimator based on deep generative neural networks. By modeling data normally distributed around a manifold of reduced dimension, we show how the power of bidirectional generative neural networks (e.g., cycleGAN) can be exploited for explicit evaluation of the data density.

Qiao Liu, Jiaze Xu, Rui Jiang, Wing Hung Wong

Proceedings of the National Academy of Sciences (PNAS), 2021, 18(15):e2101344118

Simultaneous deep generative modeling and clustering of single-cell genomic data

We proposed scDEC, a computational tool for single cell data analysis with deep generative neural networks. scDEC is built on a pair of generative adversarial networks (GANs), and is capable of learning the latent representation and inferring the cell labels, simultaneously.

Qiao Liu, Shengquan Chen, Rui Jiang, Wing Hung Wong

Nature Machine Intelligence, 2021, 3(6):536-544.

Cancer drug response prediction via a hybrid graph convolutional network

DeepCDR is a hybrid graph convolutional network consisting of a uniform graph convolutional network (UGCN) and multiple subnetworks. Unlike prior studies modeling hand-crafted features of drugs, DeepCDR automatically learns the latent representation of topological structures among atoms and bonds of drugs.

Qiao Liu, Zhiqiang Hu, Rui Jiang and Mu Zhou

Bioinformatics, 2021, 36(S2):i911–i918

Invited presentation at ECCB2020

hicGAN Infers Super Resolution Hi-C Data with Generative Adversarial Networks

We proposed hicGAN for inferring high resolution Hi-C data from low resolution Hi-C data with generative adversarial networks (GANs). To the best of our knowledge, this is the first study to apply GANs to 3D genome analysis.

Qiao Liu, Hairong Lv, Rui Jiang

Bioinformatics, 2019, 35(14):i99–i107

Invited presentation at ISMB2019

 

Full List

  1. Deep generative modeling and clustering of single cell Hi-C data
    Qiao Liu, Wanwen Zeng, Wei Zhang, Sicheng Wang, Hongyang Chen, Rui Jiang, Mu Zhou and Shaoting Zhang
    bioRxiv 2022
  2. DeepDrug: A general graph-based deep learning framework for drug-drug interactions and drug-target interactions prediction
    Qijin Yin, Xusheng Cao, Rui Fan, Qiao Liu*, Rui Jiang*, Wanwen Zeng*
    bioRxiv 2022
  3. Graph Convolutional Networks for Multi-modality Medical Imaging: Methods, Architectures, and Clinical Applications
    Kexin Ding, Mu Zhou, Zichen Wang, Qiao Liu, Corey W. Arnold, Shaoting Zhang, Dimitri N. Metaxas
    bioRxiv 2022
  4. Multimodal single cell data integration challenge: results and lessons learned
    Christopher Lance, Malte D Luecken, Daniel B Burkhardt,..., Qiao Liu,...,Fabian J Theis
    bioRxiv 2022
  5. Regulatory analysis of single cell multiome gene expression and chromatin accessibility data with scREG
    Zhana Duren, Fengge Chang, Fnu Naqing, Jingxue Xin, Qiao Liu, Wing Hung Wong
    Genome Biology 2022
  6. AggEnhance: Aggregation Enhancement by Class Interior Points in Federated Learning with Non-IID Data
    Jinxiang Ou, Yunheng Shen, Feng Wang, Qiao Liu, Xuegong Zhang, Hairong Lv
    ACM Transactions on Intelligent Systems and Technology 2022
  7. scGraph: a graph neural network-based approach to automatically identify cell types
    Qijin Yin, Qiao Liu, Zhuoran Fu, Rui Jiang
    Bioinformatics 2022
  8. DualGCN: a dual graph convolutional network model to predict cancer drug response
    Tianxing Ma, Qiao Liu, Haochen Li, Mu Zhou, Rui Jiang, Xuegong Zhang
    BMC bioinformatics 2022
  9. DeepCAGE: incorporating transcription factors in genome-wide prediction of chromatin accessibility
    Qiao Liu, Kui Hua, Xuegong Zhang, Wing Hung Wong, Rui Jiang
    Genomics, Proteomics & Bioinformatics 2022 [Code]
  10. Boost Neural Networks by Checkpoints
    Feng Wang, Guoyizhe Wei, Qiao Liu, Jinxiang Ou, Xian Wei, Hairong Lv
    NeurIPS 2021
  11. OpenAnnotate: a web server to annotate the chromatin accessibility of genomic regions
    Shengquan Chen, Qiao Liu, Xuejian Cui, Rui Jiang
    Nucleic Acids Research 2021
  12. Simultaneous deep generative modeling and clustering of single cell genomic data
    Qiao Liu, Shengquan Chen, Rui Jiang and Wing Hung Wong
    Nature Machine Intelligence 2021 [Abstract][PDF][Code]
  13. Density estimation using deep generative neural networks
    Qiao Liu, Jiaze Xu, Rui Jiang and Wing Hung Wong
    Proceedings of the National Academy of Sciences of the United States of America 2021 [Abstract][PDF][Code]
  14. Cancer Drug Response Prediction via a Hybrid Graph Convolutional Network
    Qiao Liu, Zhiqiang Hu, Rui Jiang and Mu Zhou
    Bioinformatics 2020 [Abstract][PDF][Code]
  15. Feature-Enhanced Graph Networks for Genetic Mutational Prediction Using Histopathological Images in Colon Cancer
    Kexin Ding, Qiao Liu, Edward Lee, Mu Zhou, Aidong Lu, Shaoting Zhang
    MICCAI 2020
  16. A Decentralized Systemfor Medical Data Management via Blockchain
    Qingzhu Yang, Qiao Liu, Hairong Lv
    Journal of Internet Technology 2020
  17. Mstree: A Multispecies Coalescent Approach for Estimating Ancestral Population Size and Divergence Time During Speciation with Gene Flow
    Junfeng Liu, Qiao Liu, Qingzhu Yang
    Genome Biology and Evolution 2020
  18. Quantifying Functional Impacts of Regulatory Variants with Multi-task Bayesian Neural Network
    Chencheng Xu, Qiao Liu, Jianyu Zhou, Minzhu Xie, Jianxing Feng and Tao Jiang
    Bioinformatics 2019
  19. Reinforced Molecular Optimization with Neighborhood-Controlled Grammars
    Chencheng Xu, Qiao Liu, Minlie Huang, Tao Jiang
    NeurIPS 2020 [Code]
  20. hicGAN Infers Super Resolution Hi-C Data With Generative Adversarial Networks
    Qiao Liu, Hairong Lv, Rui Jiang
    ISMB/Bioinformatics 2019 [Abstract][PDF][Code]
  21. Automatically Structuring on Chinese Ultrasound Report of Cerebrovascular Diseases via Natural Language Processing
    Pengyu Chen*, Qiao Liu*, Hairong Lv and Xiaolu Fei
    IEEE Access 2019 (Co-first author)
  22. DeepHistone: a Deep Learning Approach to Predicting Histone Modifications]
    Qijin Yin, Mengmeng Wu, Qiao Liu, Rui Jiang
    BMC Genomics 2019 [Code]
  23. EpiFIT: Functional Interpretation of Transcription Factors based on Combination of Sequence and Epigenetic Information
    Shaoming Song, Hongfei Cui, Qiao Liu, Rui Jiang
    Quantitative Biology 2019
  24. Chromatin Accessibility Prediction via a Hybrid Deep Convolutional Neural Network
    Qiao Liu, Fei Xia, Qijin Yin, Rui Jiang
    Bioinformatics 2018 [Abstract][PDF][Code]
  25. A Sequence-based Method to Predict the Impact of Regulatory Variants Using Random Forest
    Qiao Liu, Minxing Gan, Rui Jiang
    BMC Systems Biology 2017 [Code]
  26. Protein Folding Optimization Based on 3D off-lattice Model via an Improved Artificial Bee Colony Algorithm
    Bai Li, Mu Lin, Qiao Liu, Ya Li
    Journal of Molecular Modeling 2015 [Code]
(* denotes equal contribution)