Publications
Highlighted papers
(For a full list see below or go to Google Scholar)
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
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.
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
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
Full List
- 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 - 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 - 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 - 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 - 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 - 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 - scGraph: a graph neural network-based approach to automatically identify cell types
Qijin Yin, Qiao Liu, Zhuoran Fu, Rui Jiang
Bioinformatics 2022 - 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 - 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] - Boost Neural Networks by Checkpoints
Feng Wang, Guoyizhe Wei, Qiao Liu, Jinxiang Ou, Xian Wei, Hairong Lv
NeurIPS 2021 - OpenAnnotate: a web server to annotate the chromatin accessibility of genomic regions
Shengquan Chen, Qiao Liu, Xuejian Cui, Rui Jiang
Nucleic Acids Research 2021 - 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] - 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] - Cancer Drug Response Prediction via a Hybrid Graph Convolutional Network
Qiao Liu, Zhiqiang Hu, Rui Jiang and Mu Zhou
Bioinformatics 2020 [Abstract][PDF][Code] - 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 - A Decentralized Systemfor Medical Data Management via Blockchain
Qingzhu Yang, Qiao Liu, Hairong Lv
Journal of Internet Technology 2020 - 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 - 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 - Reinforced Molecular Optimization with Neighborhood-Controlled Grammars
Chencheng Xu, Qiao Liu, Minlie Huang, Tao Jiang
NeurIPS 2020 [Code] - hicGAN Infers Super Resolution Hi-C Data With Generative Adversarial Networks
Qiao Liu, Hairong Lv, Rui Jiang
ISMB/Bioinformatics 2019 [Abstract][PDF][Code] - 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) - DeepHistone: a Deep Learning Approach to Predicting Histone Modifications]
Qijin Yin, Mengmeng Wu, Qiao Liu, Rui Jiang
BMC Genomics 2019 [Code] - 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 - Chromatin Accessibility Prediction via a Hybrid Deep Convolutional Neural Network
Qiao Liu, Fei Xia, Qijin Yin, Rui Jiang
Bioinformatics 2018 [Abstract][PDF][Code] - 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] - 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]