Chang-Yu Hsieh

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 57

Top Topics

Top Venues

Briefings Bioinform.

J. Chem. Inf. Model.

J. Cheminformatics

Publications

Bojia Duan, Xin Sun, Chang-Yu Hsieh
Parallelized variational quantum classifier with shallow QRAM circuit. Quantum Inf. Process. 23 (3) (2024)
Jike Wang, Rui Qin, Mingyang Wang, Meijing Fang, Yangyang Zhang, Yuchen Zhu, Qun Su, Qiaolin Gou, Chao Shen, Odin Zhang, Zhenxing Wu, Dejun Jiang, Xujun Zhang, Huifeng Zhao, Xiaozhe Wan, Zhourui Wu, Liwei Liu, Yu Kang, Chang-Yu Hsieh, Tingjun Hou
Token-Mol 1.0: Tokenized drug design with large language model. CoRR (2024)
Lijun Liu, Jiali Yang, Jianfei Song, Xinglin Yang, Lele Niu, Zeqi Cai, Hui Shi, Tingjun Hou, Chang-Yu Hsieh, Weiran Shen, Yafeng Deng
AAVDiff: Experimental Validation of Enhanced Viability and Diversity in Recombinant Adeno-Associated Virus (AAV) Capsids through Diffusion Generation. CoRR (2024)
Odin Zhang, Haitao Lin, Hui Zhang, Huifeng Zhao, Yufei Huang, Yuansheng Huang, Dejun Jiang, Chang-Yu Hsieh, Peichen Pan, Tingjun Hou
Deep Lead Optimization: Leveraging Generative AI for Structural Modification. CoRR (2024)
Mingyang Wang, Zhengjian Wu, Jike Wang, Gaoqi Weng, Yu Kang, Peichen Pan, Dan Li, Yafeng Deng, Xiaojun Yao, Zhitong Bing, Chang-Yu Hsieh, Tingjun Hou
Genetic Algorithm-Based Receptor Ligand: A Genetic Algorithm-Guided Generative Model to Boost the Novelty and Drug-Likeness of Molecules in a Sampling Chemical Space. J. Chem. Inf. Model. 64 (4) (2024)
Ruofan Jin, Qing Ye, Jike Wang, Zheng Cao, Dejun Jiang, Tianyue Wang, Yu Kang, Wanting Xu, Chang-Yu Hsieh, Tingjun Hou
AttABseq: an attention-based deep learning prediction method for antigen-antibody binding affinity changes based on protein sequences. Briefings Bioinform. 25 (4) (2024)
Yue Guo, Haitao Hu, Wenbo Chen, Hao Yin, Jian Wu, Chang-Yu Hsieh, Qiaojun He, Ji Cao
SynergyX: a multi-modality mutual attention network for interpretable drug synergy prediction. Briefings Bioinform. 25 (2) (2024)
Yiheng Zhu, Zitai Kong, Jialu Wu, Weize Liu, Yuqiang Han, Mingze Yin, Hongxia Xu, Chang-Yu Hsieh, Tingjun Hou
Generative AI for Controllable Protein Sequence Design: A Survey. CoRR (2024)
Mingze Yin, Hanjing Zhou, Yiheng Zhu, Miao Lin, Yixuan Wu, Jialu Wu, Hongxia Xu, Chang-Yu Hsieh, Tingjun Hou, Jintai Chen, Jian Wu
Multi-Modal CLIP-Informed Protein Editing. CoRR (2024)
Wenjia Qian, Xiaorui Wang, Yu Kang, Peichen Pan, Tingjun Hou, Chang-Yu Hsieh
A general model for predicting enzyme functions based on enzymatic reactions. J. Cheminformatics 16 (1) (2024)
Odin Zhang, Yufei Huang, Shichen Cheng, Mengyao Yu, Xujun Zhang, Haitao Lin, Yundian Zeng, Mingyang Wang, Zhenxing Wu, Huifeng Zhao, Zaixi Zhang, Chenqing Hua, Yu Kang, Sunliang Cui, Peichen Pan, Chang-Yu Hsieh, Tingjun Hou
Deep Geometry Handling and Fragment-wise Molecular 3D Graph Generation. CoRR (2024)
Chao Shen, Jianfei Song, Chang-Yu Hsieh, Dong-Sheng Cao, Yu Kang, Wenling Ye, Zhenxing Wu, Jike Wang, Odin Zhang, Xujun Zhang, Hao Zeng, Heng Cai, Yu Chen, Linkang Chen, Hao Luo, Xinda Zhao, Tianye Jian, Tong Chen, Dejun Jiang, Mingyang Wang, Qing Ye, Jialu Wu, Hongyan Du, Hui Shi, Yafeng Deng, Tingjun Hou
DrugFlow: An AI-Driven One-Stop Platform for Innovative Drug Discovery. J. Chem. Inf. Model. 64 (14) (2024)
Jiebin Fang, Churu Mao, Yuchen Zhu, Xiaoming Chen, Chang-Yu Hsieh, Zhongjun Ma
Human-level molecular optimization driven by mol-gene evolution. CoRR (2024)
Odin Zhang, Tianyue Wang, Gaoqi Weng, Dejun Jiang, Ning Wang, Xiaorui Wang, Huifeng Zhao, Jialu Wu, Ercheng Wang, Guangyong Chen, Yafeng Deng, Peichen Pan, Yu Kang, Chang-Yu Hsieh, Tingjun Hou
Learning on topological surface and geometric structure for 3D molecular generation. Nat. Comput. Sci. 3 (10) (2023)
Zaixi Zhang, Qi Liu, Chee-Kong Lee, Chang-Yu Hsieh, Enhong Chen
An Equivariant Generative Framework for Molecular Graph-Structure Co-Design. CoRR (2023)
Jonathan P. Mailoa, Zhaofeng Ye, Jiezhong Qiu, Chang-Yu Hsieh, Shengyu Zhang
Protein-Ligand Complex Generator & Drug Screening via Tiered Tensor Transform. CoRR (2023)
Zhenxing Wu, Jihong Chen, Yitong Li, Yafeng Deng, Haitao Zhao, Chang-Yu Hsieh, Tingjun Hou
From Black Boxes to Actionable Insights: A Perspective on Explainable Artificial Intelligence for Scientific Discovery. J. Chem. Inf. Model. 63 (24) (2023)
Yue Wan, Jialu Wu, Tingjun Hou, Chang-Yu Hsieh, Xiaowei Jia
From molecules to scaffolds to functional groups: building context-dependent molecular representation via multi-channel learning. CoRR (2023)
Yiheng Zhu, Zhenqiu Ouyang, Ben Liao, Jialu Wu, Yixuan Wu, Chang-Yu Hsieh, Tingjun Hou, Jian Wu
MolHF: A Hierarchical Normalizing Flow for Molecular Graph Generation. IJCAI (2023)
Yanqing Duan, Li Fu, Xiao-Chen Zhang, Teng-Zhi Long, Yuan-Hang He, Zhao-Qian Liu, Ai-Ping Lu, Yafeng Deng, Chang-Yu Hsieh, Tingjun Hou, Dong-Sheng Cao
Prediction by Transferring Knowledge from Low-Fidelity Data. J. Chem. Inf. Model. 63 (8) (2023)
Jike Wang, Yundian Zeng, Huiyong Sun, Junmei Wang, Xiaorui Wang, Ruofan Jin, Mingyang Wang, Xujun Zhang, Dong-Sheng Cao, Xi Chen, Chang-Yu Hsieh, Tingjun Hou
Molecular Generation with Reduced Labeling through Constraint Architecture. J. Chem. Inf. Model. 63 (11) (2023)
Shi-Xin Zhang, Jonathan Allcock, Zhou-Quan Wan, Shuo Liu, Jiace Sun, Hao Yu, Xing-Han Yang, Jiezhong Qiu, Zhaofeng Ye, Yu-Qin Chen, Chee-Kong Lee, Yi-Cong Zheng, Shao-Kai Jian, Hong Yao, Chang-Yu Hsieh, Shengyu Zhang
TensorCircuit: a Quantum Software Framework for the NISQ Era. Quantum 7 (2023)
Odin Zhang, Jintu Zhang, Jieyu Jin, Xujun Zhang, Renling Hu, Chao Shen, Hanqun Cao, Hongyan Du, Yu Kang, Yafeng Deng, Furui Liu, Guangyong Chen, Chang-Yu Hsieh, Tingjun Hou
ResGen is a pocket-aware 3D molecular generation model based on parallel multiscale modelling. Nat. Mac. Intell. 5 (9) (2023)
Yuwei Yang, Chang-Yu Hsieh, Yu Kang, Tingjun Hou, Huanxiang Liu, Xiaojun Yao
Deep Generation Model Guided by the Docking Score for Active Molecular Design. J. Chem. Inf. Model. 63 (10) (2023)
Yiheng Zhu, Jialu Wu, Chaowen Hu, Jiahuan Yan, Chang-Yu Hsieh, Tingjun Hou, Jian Wu
Sample-efficient Multi-objective Molecular Optimization with GFlowNets. CoRR (2023)
Yiheng Zhu, Zhenqiu Ouyang, Ben Liao, Jialu Wu, Yixuan Wu, Chang-Yu Hsieh, Tingjun Hou, Jian Wu
MolHF: A Hierarchical Normalizing Flow for Molecular Graph Generation. CoRR (2023)
Xujun Zhang, Odin Zhang, Chao Shen, Wanglin Qu, Shicheng Chen, Hanqun Cao, Yu Kang, Zhe Wang, Ercheng Wang, Jintu Zhang, Yafeng Deng, Furui Liu, Tianyue Wang, Hongyan Du, Langcheng Wang, Peichen Pan, Guangyong Chen, Chang-Yu Hsieh, Tingjun Hou
Efficient and accurate large library ligand docking with KarmaDock. Nat. Comput. Sci. 3 (9) (2023)
Lixue Cheng, Ziyi Yang, Benben Liao, Chang-Yu Hsieh, Shengyu Zhang
ODBO: Bayesian Optimization with Search Space Prescreening for Directed Protein Evolution. CoRR (2022)
Yuwei Yang, Zhenxing Wu, Xiaojun Yao, Yu Kang, Tingjun Hou, Chang-Yu Hsieh, Huanxiang Liu
Exploring Low-Toxicity Chemical Space with Deep Learning for Molecular Generation. J. Chem. Inf. Model. 62 (13) (2022)
Yue Wan, Chang-Yu Hsieh, Ben Liao, Shengyu Zhang
Retroformer: Pushing the Limits of End-to-end Retrosynthesis Transformer. ICML (2022)
Dejun Jiang, Huiyong Sun, Jike Wang, Chang-Yu Hsieh, Yuquan Li, Zhenxing Wu, Dong-Sheng Cao, Jian Wu, Tingjun Hou
Out-of-the-box deep learning prediction of quantum-mechanical partial charges by graph representation and transfer learning. Briefings Bioinform. 23 (2) (2022)
Zhenxing Wu, Dejun Jiang, Jike Wang, Xujun Zhang, Hongyan Du, Lurong Pan, Chang-Yu Hsieh, Dongsheng Cao, Tingjun Hou
Knowledge-based BERT: a method to extract molecular features like computational chemists. Briefings Bioinform. 23 (3) (2022)
Yu-Qin Chen, Yu Chen, Chee-Kong Lee, Shengyu Zhang, Chang-Yu Hsieh
Optimizing quantum annealing schedules with Monte Carlo tree search enhanced with neural networks. Nat. Mach. Intell. 4 (3) (2022)
Zi-Yi Yang, Zhaofeng Ye, Yijia Xiao, Chang-Yu Hsieh, Sheng-Yu Zhang
SPLDExtraTrees: robust machine learning approach for predicting kinase inhibitor resistance. Briefings Bioinform. 23 (3) (2022)
Mingyang Wang, Jike Wang, Gaoqi Weng, Yu Kang, Peichen Pan, Dan Li, Yafeng Deng, Honglin Li, Chang-Yu Hsieh, Tingjun Hou
ReMODE: a deep learning-based web server for target-specific drug design. J. Cheminformatics 14 (1) (2022)
Jialu Wu, Junmei Wang, Zhenxing Wu, Shengyu Zhang, Yafeng Deng, Yu Kang, Dong-Sheng Cao, Chang-Yu Hsieh, Tingjun Hou
ALipSol: An Attention-Driven Mixture-of-Experts Model for Lipophilicity and Solubility Prediction. J. Chem. Inf. Model. 62 (23) (2022)
Yuquan Li, Chang-Yu Hsieh, Ruiqiang Lu, Xiaoqing Gong, Xiaorui Wang, Pengyong Li, Shuo Liu, Yanan Tian, Dejun Jiang, Jiaxian Yan, Qifeng Bai, Huanxiang Liu, Shengyu Zhang, Xiaojun Yao
An adaptive graph learning method for automated molecular interactions and properties predictions. Nat. Mach. Intell. 4 (7) (2022)
Yue Wan, Benben Liao, Chang-Yu Hsieh, Shengyu Zhang
Retroformer: Pushing the Limits of Interpretable End-to-end Retrosynthesis Transformer. CoRR (2022)
Ziyi Yang, Zhaofeng Ye, Yijia Xiao, Chang-Yu Hsieh
SPLDExtraTrees: Robust machine learning approach for predicting kinase inhibitor resistance. CoRR (2021)
Zhenxing Wu, Dejun Jiang, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Dong-Sheng Cao, Tingjun Hou
Hyperbolic relational graph convolution networks plus: a simple but highly efficient QSAR-modeling method. Briefings Bioinform. 22 (5) (2021)
Guo-Li Xiong, Zhenxing Wu, Jia-Cai Yi, Li Fu, Zhi-Jiang Yang, Chang-Yu Hsieh, Mingzhu Yin, Xiangxiang Zeng, Chengkun Wu, Ai-Ping Lu, Xiang Chen, Tingjun Hou, Dong-Sheng Cao
ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties. Nucleic Acids Res. 49 (Webserver-Issue) (2021)
Yijia Xiao, Jiezhong Qiu, Ziang Li, Chang-Yu Hsieh, Jie Tang
Modeling Protein Using Large-scale Pretrain Language Model. CoRR (2021)
Jike Wang, Chang-Yu Hsieh, Mingyang Wang, Xiaorui Wang, Zhenxing Wu, Dejun Jiang, Benben Liao, Xujun Zhang, Bo Yang, Qiaojun He, Dongsheng Cao, Xi Chen, Tingjun Hou
Multi-constraint molecular generation based on conditional transformer, knowledge distillation and reinforcement learning. Nat. Mach. Intell. 3 (10) (2021)
Junsheng Kong, Weizhao Li, Ben Liao, Jiezhong Qiu, Chang-Yu Hsieh, Yi Cai, Jinhui Zhu, Shengyu Zhang
Learning Large-scale Network Embedding from Representative Subgraph. CoRR (2021)
Shi-Xin Zhang, Chang-Yu Hsieh, Shengyu Zhang, Hong Yao
Neural predictor based quantum architecture search. Mach. Learn. Sci. Technol. 2 (4) (2021)
Dejun Jiang, Zhenxing Wu, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Zhe Wang, Chao Shen, Dong-Sheng Cao, Jian Wu, Tingjun Hou
Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models. J. Cheminformatics 13 (1) (2021)
Pengyong Li, Yuquan Li, Chang-Yu Hsieh, Shengyu Zhang, Xianggen Liu, Huanxiang Liu, Sen Song, Xiaojun Yao
TrimNet: learning molecular representation from triplet messages for biomedicine. Briefings Bioinform. 22 (4) (2021)
Xiao-Chen Zhang, Chengkun Wu, Zhi-Jiang Yang, Zhen-Xing Wu, Jia-Cai Yi, Chang-Yu Hsieh, Tingjun Hou, Dong-Sheng Cao
MG-BERT: leveraging unsupervised atomic representation learning for molecular property prediction. Briefings Bioinform. 22 (6) (2021)
Junsheng Kong, Weizhao Li, Zeyi Liu, Ben Liao, Jiezhong Qiu, Chang-Yu Hsieh, Yi Cai, Shengyu Zhang
Fast Extraction of Word Embedding from Q-contexts. CIKM (2021)
Junsheng Kong, Weizhao Li, Zeyi Liu, Ben Liao, Jiezhong Qiu, Chang-Yu Hsieh, Yi Cai, Shengyu Zhang
Fast Extraction of Word Embedding from Q-contexts. CoRR (2021)
Jonathan Allcock, Chang-Yu Hsieh
Quantum algorithm for training nonlinear SVMs in almost linear time. CoRR (2020)
Jonathan Allcock, Chang-Yu Hsieh
A quantum extension of SVM-perf for training nonlinear SVMs in almost linear time. Quantum 4 (2020)
Guangyong Chen, Pengfei Chen, Yujun Shi, Chang-Yu Hsieh, Benben Liao, Shengyu Zhang
Rethinking the Usage of Batch Normalization and Dropout in the Training of Deep Neural Networks. CoRR (2019)
Guangyong Chen, Pengfei Chen, Chang-Yu Hsieh, Chee-Kong Lee, Benben Liao, Renjie Liao, Weiwen Liu, Jiezhong Qiu, Qiming Sun, Jie Tang, Richard S. Zemel, Shengyu Zhang
Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models. CoRR (2019)
Pengfei Chen, Weiwen Liu, Chang-Yu Hsieh, Guangyong Chen, Shengyu Zhang
Utilizing Edge Features in Graph Neural Networks via Variational Information Maximization. CoRR (2019)
Jonathan Allcock, Chang-Yu Hsieh, Iordanis Kerenidis, Shengyu Zhang
Quantum algorithms for feedforward neural networks. CoRR (2018)
Chen-Fu Chiang, Chang-Yu Hsieh
Resonant transition-based quantum computation. Quantum Inf. Process. 16 (5) (2017)
Chang-Yu Hsieh, Raymond Kapral
Correlation Functions in Open Quantum-Classical Systems. Entropy 16 (1) (2014)