publications

2023

1. arXiv

   GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?

   Mufei Li, Eleonora Kreačić, Vamsi K. Potluru, and Pan Li

   arXiv preprint arXiv:2310.13833, 2023

   arXiv Bib Code

   @article{li2023graphmaker,
     title = {GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?},
     author = {Li, Mufei and Kreačić, Eleonora and Potluru, Vamsi K. and Li, Pan},
     year = {2023},
     journal = {arXiv preprint arXiv:2310.13833},
   }

2022

1. Mol. Inf.

   Benchmarking Accuracy and Generalizability of Four Graph Neural Networks Using Large In Vitro ADME Datasets from Different Chemical Spaces

   Fabio Broccatelli, Richard Trager, Michael Reutlinger, George Karypis, and Mufei Li

   Molecular Informatics, 2022

   Bib HTML Code

   @article{https://doi.org/10.1002/minf.202100321,
     title = {Benchmarking Accuracy and Generalizability of Four Graph Neural Networks Using Large In Vitro ADME Datasets from Different Chemical Spaces},
     author = {Broccatelli, Fabio and Trager, Richard and Reutlinger, Michael and Karypis, George and Li, Mufei},
     year = {2022},
     journal = {Molecular Informatics},
     volume = {41},
     number = {8},
     pages = {2100321},
     doi = {10.1002/minf.202100321},
   }

2. Sci. Rep.

   CTKG: A Knowledge Graph for Clinical Trials

   Ziqi Chen, Bo Peng, Vasileios Ioannidis, Mufei Li, George Karypis, and Xia Ning

   Scientific Reports, 2022

   Bib HTML Code

   @article{CTKG,
     title = {CTKG: A Knowledge Graph for Clinical Trials},
     author = {Chen, Ziqi and Peng, Bo and Ioannidis, Vasileios and Li, Mufei and Karypis, George and Ning, Xia},
     year = {2022},
     journal = {Scientific Reports},
     volume = {12},
     number = {1},
     doi = {10.1038/s41598-022-08454-z},
   }

2021

1. Brief. Bioinform.

   De novo generation of dual-target ligands using adversarial training and reinforcement learning

   Fengqing Lu, Mufei Li, Xiaoping Min, Chunyan Li, and Xiangxiang Zeng

   Briefings in Bioinformatics, 2021

   Bib HTML

   @article{DLGN,
     title = {De novo generation of dual-target ligands using adversarial training and reinforcement learning},
     author = {Lu, Fengqing and Li, Mufei and Min, Xiaoping and Li, Chunyan and Zeng, Xiangxiang},
     year = {2021},
     journal = {Briefings in Bioinformatics},
     volume = {22},
     issue = {6},
     doi = {10.1093/bib/bbab333},
   }

2. ACS Omega

   DGL-LifeSci: An Open-Source Toolkit for Deep Learning on Graphs in Life Science

   Mufei Li, Jinjing Zhou, Jiajing Hu, Wenxuan Fan, Yangkang Zhang, Yaxin Gu, and George Karypis

   ACS Omega, 2021

   Bib HTML Code

   @article{dgllife,
     title = {DGL-LifeSci: An Open-Source Toolkit for Deep Learning on Graphs in Life Science},
     author = {Li, Mufei and Zhou, Jinjing and Hu, Jiajing and Fan, Wenxuan and Zhang, Yangkang and Gu, Yaxin and Karypis, George},
     year = {2021},
     journal = {ACS Omega},
     volume = {6},
     number = {41},
     pages = {27233-27238},
     doi = {10.1021/acsomega.1c04017},
     dimensions = {false},
   }

2020

1. DRKG - Drug Repurposing Knowledge Graph for Covid-19

   Vassilis N. Ioannidis, Xiang Song, Saurav Manchanda, Mufei Li, Xiaoqin Pan, Da Zheng, Xia Ning, Xiangxiang Zeng, and George Karypis

   2020

   Bib HTML Code

   @misc{drkg2020,
     title = {DRKG - Drug Repurposing Knowledge Graph for Covid-19},
     author = {Ioannidis, Vassilis N. and Song, Xiang and Manchanda, Saurav and Li, Mufei and Pan, Xiaoqin and Zheng, Da and Ning, Xia and Zeng, Xiangxiang and Karypis, George},
     year = {2020},
   }

2019

1. arXiv

   Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks

   Minjie Wang, Da Zheng, Zihao Ye, Quan Gan, Mufei Li, Xiang Song, Jinjing Zhou, Chao Ma, Lingfan Yu, Yu Gai, Tianjun Xiao, Tong He, George Karypis, Jinyang Li, and Zheng Zhang

   arXiv preprint arXiv:1909.01315, 2019

   arXiv Bib Code

   @article{wang2019dgl,
     title = {Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks},
     author = {Wang, Minjie and Zheng, Da and Ye, Zihao and Gan, Quan and Li, Mufei and Song, Xiang and Zhou, Jinjing and Ma, Chao and Yu, Lingfan and Gai, Yu and Xiao, Tianjun and He, Tong and Karypis, George and Li, Jinyang and Zhang, Zheng},
     year = {2019},
     journal = {arXiv preprint arXiv:1909.01315},
   }

2. ICLR workshop

   A statistical characterization of attentions in graph neural networks

   Mufei Li, Hao Zhang, Xingjian Shi, Minjie Wang, and Zheng Zhang

   International Conference on Learning Representations (ICLR) 2019 Workshop on Representation Learning on Graphs and Manifolds, 2019

   Bib HTML

   @article{GAT_stats,
     title = {A statistical characterization of attentions in graph neural networks},
     author = {Li, Mufei and Zhang, Hao and Shi, Xingjian and Wang, Minjie and Zhang, Zheng},
     year = {2019},
     journal = {International Conference on Learning Representations (ICLR) 2019 Workshop on Representation Learning on Graphs and Manifolds},
   }