Currently I am a Postdoctoral Scholar at Tsinghua University, cooperate with Prof.Qiangfeng Cliff Zhang.
I am broadly interested in deep learning, with data-driven algorithm design and applications in real world (2D/3D computer vision and graphics) and micro world (Electron Cryo-Microscopy Density map based Molecular Structure Determination, Single Cell Clustering and RNA Structure Understanding). My recent research focuses on designing algorithms and deep learning models to gain biological insights from advances in the
large data sets.
Prior to Ph.D. student period, I was a visiting scholar at the Chinese University of Hong Kong, collaborating with awesome folks in the lab of
Prof. Xiaogang Wang. I also works closely with Zhe Wang,
Jianping Shi and Hongsheng Li, focusing on 3D Object Detection and
Molecular structure model building.
I received my Ph.D. degree in School of Life Sciences of Tsinghua University in 2021, supervised by Prof.Qiangfeng Cliff Zhang. Before I came to Tsinghua University, I received a master and bachelor degree in Computer Science in Tianjin Polytechnic University in 2016 and 2013, respectively.
Feel free to say hi: xukui at tsinghua.edu.cn
What's New
[May 2023] One paper accepted to Nucleic Acids Research, congratulations to Yiran and Lei.
[Apr 2023] One paper accepted to Cell, congratulations to Prof Gao and Li.
[Mar 2023] One paper accepted to Journal of Molecular Biology, congratulations to Muzhi.
[Nov 2022] Our PrismNet method paper won the 2021 Sanofi-Cell Research Outstanding Research Article Award.
[Feb 2022] Our PrismNet method paper was awarded as the Top Ten Advances of 2021 in Bioinformatics in China by Genomics, Proteomics and Bioinformatics (GPB).
[Oct 2021] One paper accepted to Nature Machine Intelligence, congratulations to Dr. Jing Gong.
[Jul 2021] CryoNet (https://cryonet.ai) is online!
[Jan 2021] One paper accepted to Science. Proud to apply our improved A2-Net to identify new proteins in Spliceosome,
congratulations to Dr. Rui Bai and Dr. Ruixue Wan.
[Jan 2021] Our PrismNet method paper accepted to Cell Research, congratulations to all the team members.
[Nov 2020] Our PrismNet Prediction on SARS-CoV-2 paper accepted to Cell, congratulations to Dr. Lei Sun, Pan Li and Wenze.
[Oct 2020] One paper accepted to Nucleic Acids Research, congratulations to Pan Li and Xiaolin.
[Jul 2020] One paper accepted to Bioinformatics.
[Jul 2020] Proud to apply our PrismNet to predict host cell target proteins bind to SARS-CoV-2 RNA! Paper out on BioRxiv.
[May 2020] PrismNet method paper out on BioRxiv: Predicting dynamic cellular protein-RNA interactions using deep learning and in vivo RNA structure,
code are available at Github.
[Jan 2020] One paper accepted to ICRA 2020, congratulations to Hongwei Yi.
[Oct 2019] Paper out on Nature Communications: SCALE method for single-cell ATAC-seq analysis via latent feature extraction, code are available at SCALE.
[Mar 2019] Paper out on BioRxiv: VRmol: an Integrative Cloud-Based Virtual Reality System to Explore Macromolecular Structure, code are available
at VRmol.
[Jan 2019] Presented our work A2-Net at AAAI 2019, Hawaii.
Research
PrismNet: predicting protein–RNA interaction using in vivo RNA structural information
Yiran Xu*, Jianghui Zhu*, Wenze Huang*, Kui Xu, Rui Yang, Qiangfeng cliff Zhang#, Lei Sun#
Structural basis of membrane skeleton organization in red blood cells
Ningning Li#*, Siyi Chen*, Kui Xu, Meng-Ting He, Meng-Qiu Dong, Qiangfeng Cliff Zhang, and Ning Gao#
CryoRes: Local Resolution Estimation of Cryo-EM Density Maps by Deep Learning
Muzhi Dai, Zhuoer Dong, Kui Xu#, and Qiangfeng Cliff Zhang#
A deep learning method for recovering missing signals in transcriptome-wide RNA structure profiles from probing
experiments
Jing Gong*, Kui Xu*, Ziyuan Ma, Zhi John Lu and Qiangfeng Cliff Zhang
In vivo structural characterization of the whole SARS-CoV-2 RNA genome identifies host cell target proteins vulnerable to re-purposed drugs
Lei Sun*, Pan Li*, Xiaohui Ju*, Jian Rao*, Wenze Huang*, Shaojun Zhang, Tuanlin Xiong, Kui Xu, Xiaolin Zhou, Lili Ren, Qiang Ding#, Jianwei Wang# and Qiangfeng Cliff Zhang#
Predicting dynamic cellular protein-RNA interactions using deep learning and in vivo RNA structure
Lei Sun*, Kui Xu*, Wenze Huang*, Yucheng T. Yang*, Pan Li, Lei Tang, Tuanlin Xiong and Qiangfeng Cliff Zhang
Structure of the activated human minor spliceosome
Rui Bai*, Ruixue Wan*, Lin Wang, Kui Xu, Qiangfeng Cliff Zhang, Jianlin Lei, and Yigong Shi
RASP: an atlas of transcriptome-wide RNA secondary structure probing data
Pan Li*, Xiaolin Zhou*, Kui Xu, and Qiangfeng Cliff Zhang
VRmol: an Integrative Web-Based Virtual Reality System to Explore Macromolecular Structure
Kui Xu*, Nan Liu*, Jingle Xu, Chunlong Guo, Lingyun Zhao, Hong-Wei Wang and Qiangfeng Cliff Zhang
SCALE method for single-cell ATAC-seq analysis via latent feature extraction
Lei Xiong, Kui Xu, Kang Tian, Yanqiu Shao, Lei Tang, Ge Gao, Michael Zhang, Tao Jiang and Qiangfeng Cliff Zhang
A2-Net: Molecular Structure Estimation from Cryo-EM Density Volumes
Kui Xu, Zhe Wang, Jianping Shi, Hongsheng Li and Qiangfeng Cliff Zhang
SegVoxelNet: Exploring Semantic Context and Depth-aware Features for 3D Vehicle Detection from Point Cloud
Hongwei Yi, Shaoshuai Shi, Mingyu Ding, Jiankai Sun, Kui Xu, Hui Zhou, Zhe Wang, Sheng Li and Guoping Wang
Bioactive functionalized monolayer graphene for high-resolution cryo-electron microscopy
Nan Liu, Jincan Zhang, Yanan Chen, Chuan Liu, Xing Zhang, Kui Xu, Jie Wen, Zhipu Luo, Shulin Chen, Peng Gao, Kaicheng Jia, Zhongfan Liu, Hailin Peng and Hong-Wei Wang
RISE: a database of RNA interactome from sequencing experiments
Jing Gong*, Di Shao*, Kui Xu, Zhipeng Lu, Zhi John Lu, Yucheng T. Yang and Qiangfeng Cliff Zhang
Reweighted sparse subspace clustering
Jun Xu, Kui Xu, Ke Chen and Jishou Ruan
(* co-First authors; # co-Corresponding authors)
Open Source
PrismNet, a deep learning tool that integrates experimental in vivo RNA structure data and RBP binding data for matched cells to accurately predict dynamic
RBP binding in various cellular conditions.
VRmol provides the visualization and analysis of macromolecule structures in an infinite virtual environment on the web. VRmol is natively built with
WebXR technology, providing functions in a fully immersive, inspiring virtual environment.
Kitti Object Visualization
Data Transformation and Visualization for
Kitti Object Detection Dataset, including mapping 3D boxes on LiDar point cloud in
volumetric mode, mapping 2D and 3D boxes on Camera image, mapping 2D boxes on LiDar Birdview and mapping LiDar data on Camera image.
Implementing a 3D
DenseNet for 3D CAD Object Classification on
ModelNet dataset using highly
efficient
Torch. VoxNet, C3D, and 3D-VGG models are also provided. Multi-GPU training is well supported. Check
ModelNet Benchmark Leaderboard to see related researches.
A collaborative list of 3D Deep Learning works via 3D Representation, 3D Classification, 3D Classification, 3D Object Detection, 3D Reconstruction & Generation, 3D Human Pose Estimation and their related datasets.
A collaborative list of awesome CryoEM (Electron Cryo-Microscopy) resources, including Methods and Softwares related Particle Picking, 3D Classification, Denoising, Motion Correction, 3D Reconstruction, Model Building and some other related research.
V. Falconieri, S. Subramaniam, NCI-NIH
Academic Lectures
Deep learning based model building methods for Cryo-EM Density Map
Dec. 07 - Dec. 09 2020Beijing, China
Machine Intelligence Methods for Structural Biology on Protein, RNA and DNA
Sep. 24 - Sep. 29 2020Beijing, China
A
2-Net: Molecular Structure Estimation from Cryo-EM Density Volumes
Jun. 16 - Jun. 19 2019Beijing, China
A
2-Net: Molecular Structure Estimation from Cryo-EM Density Volumes
Jan.27 - Feb.1 2019Hawaii, USA
Tools for macromolecular structure visualization and analysis: the next generation
Oct.27 - Oct. 29 2017Beijing, China
Experience
Autonomous Driving Group, SenseTime Research, Beijing, China
Oct. 2017 – Dec. 2019
MMLab, the Chinese University of Hong Kong, Hong Kong, China
Jul. 2016 – Aug. 2016
Multimedia Information Processing Lab, Peking University, Beijing, China
Jun. 2012 – Oct. 2012
