Cong Shen (申 聪)
Research Fellow
Department of Mathematics, National University of Singapore

Location: Block S17, 10 Lower Kent Ridge Road, Singapore 119076
About Me | Research Interests | Education | Publications | Conferences | Services | Projects

Email: cshen@nus.edu.sg; cshen@hnu.edu.cn;
[Google Scholar] [GitHub] [ORCID]

About Me

 I am a research fellow in Department of Mathematics, National University of Singapore (NUS). Supervisor: Prof. Fei Han. I received the Ph.D. degree in the College of Computer Science and Electronic Engineering, Hunan University (HNU), P. R. China. Supervisor: Prof. Jiawei Luo. I received funding from the China Scholarship Council and studied as a visiting student at the School of Physical & Mathematical Sciences, Nanyang Technological University since October 2021. Supervisor: Prof. Kelin Xia. I received the Bachelor degree in College of Information and Intelligence, Hunan Agricultural University, China, in 2018. My research interests are mainly in applying topological data analysis, machine learning and graph neural networks to pharmacogenomics, biological networks and materials molecule. I have published more than 20 technical papers in refered conference proceedings and journals such as Cell Reports Methods, Briefings in Bioinformatics, Bioinformatics, JBHI, BIBM, JCIM and TCBB.

Research Interests

 My research interests are mainly in applying topological data analysis, geometric deep learning and graph neural networks to pharmacogenomics, biological networks and material molecule. Currently, I focus on the following research topics:

Educational and Professional Qualifications

Publications
    [2024]

  • Yipeng Zhang, Cong Shen, Kelin Xia*, "Multi-Cover Persistence (MCP)-based machine learning for polymer property prediction," Briefings in Bioinformatics, (2024). [PDF]

  • Zhenyu Jiang, Pingjian Ding, Cong Shen*, Xiaopeng Dai*, "Geometric molecular graph representation learning model for drug-drug interactions prediction," IEEE Journal of Biomedical and Health Informatics, (2024). [PDF]

  • Zhenyu Jiang, Zhi Gong*, Xiaopeng Dai*, Hongyan Zhang, Pingjian Ding, Cong Shen*, "Deep graph contrastive learning model for drug-drug interaction prediction," Plos One, 19(6), e0304798 (2024). [PDF]

  • Cong Shen, Pingjian Ding, Junjie Wee, Jialin Bi, Jiawei Luo*, Kelin Xia*, "Curvature-enhanced Graph Convolutional Network for Biomolecular Interaction Prediction," Computational and Structural Biotechnology Journal, 23, 1016-1025 (2024). [PDF]

    • [2023]

  • Cong Shen, Jiawei Luo*, Kelin Xia*, "Molecular geometric deep learning," Cell Reports Methods, 3(11), 100621 (2023). [PDF]

  • Wenyu Shan, Cong Shen, Lingyun Luo, Pingjian Ding*, "Multi-task Learning for Predicting Synergistic Drug Combinations based on Auto-Encoding Multi-Relational Graphs," iScience, 26(10), 108020 (2023). [PDF]

  • Yichen Zhong, Cong Shen, Xiaoting Xi, Yuxun Luo, Pingjian Ding, Lingyun Luo*, "Multitask joint learning with graph autoencoders for predicting potential MiRNA-drug associations," Artificial Intelligence in Medicine, 145, 102665 (2023). [PDF]

  • Siyu Peng, Jiawei Luo*, Cong Shen, Bo Wang, "Diagnosis of Lung Cancer Subtypes by Combining Multi-graph Embedding and Graph Fusion Network," International Conference on Intelligent Computing (ICIC), 445-456 (2023). [PDF]

  • Bo Wang, Jiawei Luo*, Ying Liu*, Wanwan Shi, Zehao Xiong, Cong Shen, Yahui Long, "Spatial-MGCN: a novel multi-view graph convolutional network for identifying spatial domains with attention mechanism," Briefings in Bioinformatics, 24(5), bbad262 (2023). [PDF]

  • Hou Yee Choo, JunJie Wee*, Cong Shen, Kelin Xia*, "Fingerprint-Enhanced Graph Attention Network (FinGAT) Model for Antibiotic Discovery," Journal of Chemical Information and Modeling, 63(10), 2928–2935 (2023). [PDF]

    • [2022]

  • Zehao Xiong, Xiangtao Chen*, Jiawei Luo*, Cong Shen, Zhongyuan Xu, "scSAGAN: A scRNA-seq data imputation method based on Semi-Supervised Learning and Probabilistic Latent Semantic Analysis," IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 178-181 (2022). [PDF]

  • Yichen Zhong, Cong Shen, Huanhuan Wu, Tao Xu, Lingyun Luo*, "Improving the Prediction of Potential Kinase Inhibitors with Feature Learning on Multisource Knowledge," Interdisciplinary Sciences: Computational Life Sciences, 14, 775–785 (2022). [PDF]

  • Jiawei Luo*, Wenjue Ouyang, Cong Shen, Jie Cai, "Multi-relation graph embedding for predicting miRNA-target gene interactions by integrating gene sequence information," IEEE Journal of Biomedical and Health Informatics (JBHI) , 26(8), 4345-4353 (2022). [PDF]

    • [2021]

  • Jiawei Luo, Zihan Lai, Cong Shen, Pei Liu, Heyuan Shi*, "Graph Attention Mechanism-based Deep Tensor Factorization for Predicting disease-associated miRNA-miRNA pairs," IEEE International Conference on Bioinformatics and Biomedicine (BIBM) , 189-196 (2021). [PDF]

  • Jiawei Luo, Yaoting Bao, Xiangtao Chen*, Cong Shen, "Metapath-Based Deep Convolutional Neural Network for Predicting miRNA-Target Association on Heterogeneous Network," Interdisciplinary Sciences: Computational Life Sciences , 13(4), 547–558 (2021). [PDF]

  • Xin Chen, Lingyun Luo, Cong Shen, Pingjian Ding*, Jiawei Luo, “An In Silico Method for Predicting Drug Synergy Based on Multitask Learning,” Interdisciplinary Sciences: Computational Life Sciences , 13, 299-311, 2021. [PDF]

  • Xinru Tang, Jiawei Luo*, Cong Shen, Zihan Lai, “Multi-view Multichannel Attention Graph Convolutional Network for miRNA–disease association prediction,” Briefings in Bioinformatics, 22(6), 1-12, 2021. [PDF]

    • [2020]

  • Cong Shen, Jiawei Luo*, Wenjue Ouyang, Pingjian Ding, Xiangtao Chen, “IDDkin: network-based influence deep diffusion model for enhancing prediction of kinase inhibitors,” Bioinformatics, 36(22-23), 5481–5491, 2020. [PDF]

  • Cong Shen, Jiawei Luo*, Wenjue Ouyang, Pingjian Ding, Hao Wu, “Identification of Small Molecule–miRNA Associations with Graph Regularization Techniques in Heterogeneous Networks,” Journal of Chemical Information and Modeling, 60(12), 6709–6721, 2020. [PDF]

  • Wei Wang, Jiawei Luo*, Cong Shen, Nguye Hoang Tu, “A graph convolutional matrix completion method for miRNA-disease association prediction,” International Conference on Intelligent Computing, 201–215, 2020. [PDF]

  • Cong Shen, Jiawei Luo*,Zihan Lai, Pingjian Ding, “Multiview joint learning-based method for identifying small-molecule-associated MiRNAs by integrating pharmacological, genomics, and network knowledge,” Journal of Chemical Information and Modeling, 60(8), 4085–4097, 2020. [PDF]

  • Jiawei Luo*, Cong Shen, Zihan Lai, Jie Cai, Pingjian Ding, “Incorporating clinical, chemical and biological information for predicting small molecule-microRNA associations based on non-negative matrix factorization,” IEEE/ACM transactions on computational biology and bioinformatics, 18(6), 2535–2545, 2020. [PDF]

  • Pingjian Ding, Cong Shen, Zihan Lai, Cheng Liang, Guanghui Li, Jiawei Luo*, “Incorporating multisource knowledge to predict drug synergy based on graph co-regularization,” Journal of chemical information and modeling, 60(1), 37–46, 2020. [PDF]

    • [2019]

  • Donghui Li, Cong Shen*, Xiaopeng Dai, Xinghui Zhu, Jian Luo, Xueting Li, Haiwen Chen, Zhiyao Liang, “Research on Data Fusion of Adaptive Weighted Multi-Source Sensor,” Computers, Materials & Continua, 61(3), 1217–1231, 2019. [PDF]

  • Donghui Li, Cong Shen*, Xiaopeng Dai, Haiwen Chen, “A Kind of Agricultural Content Networking Information Fusion Method Based on Ontology,” International Conference on Cloud Computing and Security, 576–588, 2019. [PDF]

    • [2018]

  • SHEN Cong, DAI Xiao-peng and LI Dong-hui*, “A Research on Network Similarity Search Algorithm for Biological Networks,” MATEC Web of Conferences, 173,03025, 2018. [PDF]


Conferences and Presentations

  • Invited speaker: School of Mathematics and Statistics, Beijing Jiaotong University, Beijing, China, September 26, 2024.

  • Invited speaker: "The 5th Conference on Computational and Mathematical Bioinformatics and Biophysics", Tsinghua Sanya International Mathematics Forum, Sanya, China, December 11-15, 2023.

  • Invited speaker: "The 8th Qilu Youth Forum at Shandong University", Shandong University, Jinan, China, October 24-28, 2023.

  • Invited speaker: "Applied Topology and Geometry for Data Sciences", Mathematical Science Research Center, Chongqing, China, June 26-28, 2023.

  • Invited speaker: College of Information and Intelligence, Hunan Agricultural University, Changsha, China, May 25, 2023.

Services
    Journal Reviewer

  • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)

  • Neural Networks

  • IEEE Journal of Biomedical and Health Informatics (JBHI)

  • Bioinformatics

  • Journal of Molecular Biology (JMB)

  • Computers in Biology and Medicine (CIBM)

  • Journal of Molecular Graphics and Modelling (JMGM)

  • BMC Genomics

  • International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI)

  • Knowledge and Information Systems (KIS)

  • Current Pharmaceutical Design

  • Scientific Reports

  • International Journal of Biological Macromolecules

  • Bioinformatics and Biology Insights (BBI)

Projects

  • China Scholarship Council. Incorporating next generation sequencing and drug response data to predict small molecule drug-associated miRNAs and identify joint modular patterns. 2021-2023. Principal Investigator.

  • Hunan Provincial Innovation Foundation for Postgraduate. Study on prediction method of small molecule drug-related miRNA based on heterogeneous information network. 2021-2022. Principal Investigator.



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