Yahui Long

Yahui Long

Research fellow at A*STAR, Singapore

You can also find my papers on my Google Scholar profile

Conferences and Journals

  1. BingXue Du, Yahui Long, Xiaoli Li, Min Wu, and JianYu Shi. “CMMS-GCL: Cross-Modality Metabolic Stability Prediction with Graph Contrastive Learning”. Bioinformatics. 2023.
  2. Xuejing Shi, Juntong Zhu, Yahui Long*, and Cheng Liang. “Identifying spatial domains of spatially resolved transcriptomics via multi-view graph convolutional networks”. Briefings in Bioinformatics. 2023.
  3. Bo Wang, Jiawei Luo, Ying Liu, Wanwan Shi, Zehao Xiong, Cong Shen and Yahui Long. “Spatial-MGCN: a novel multi-view graph convolutional network for identifying spatial domains with attention mechanism”. Briefings in Bioinformatics. 2023.
  4. Yahui Long, Kok Siong Ang, Sha Liao, Raman Sethi, Yang Heng, Chengwei Zhong, Hang Xu, Nazihah Husna, Min Jian, Lai Guan Ng, Ao Chen, Nicholas RJ Gascoigne, Xun Xu, and Jinmiao Chen. “Integrated analysis of spatial multi-omics with SpatialGlue”. bioRxiv. 2023.
  5. Yahui Long, Kok Siong Ang, Mengwei Li, Kian Long Kelvin Chong, Raman Sethi, Chengwei Zhong, Hang Xu, Zhiwei Ong, Karishma Sachaphibulkij, Ao Chen, Zeng Li, Huazhu Fu, Min Wu, Hsiu Kim Lina Lim, Longqi Liu, Jinmiao Chen. “Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST.” Nature Communications, 14, 1155 (2023).
  6. Yahui Long, Min Wu, Yong Liu, Yuan Fang, Chee-Keong Kwoh, Jinmiao Chen, Jiawei Luo and Xiaoli Li. “Pre-training Graph Neural Networks for Link Prediction in Biomedical Networks.”
    • Journal: Bioinformatics, 2022.
  7. Yahui Long, Min Wu, Yong Liu, Jie Zheng, Chee-Keong Kwoh, Jiawei Luo and Xiaoli Li. “Graph Contextualized Attention Network for Predicting Synthetic Lethality in Human Cancers.”
  8. Yahui Long, Min Wu, Chee-Keong Kwoh, Jiawei Luo and Xiaoli Li. “Predicting Human Microbe-Drug Associations via Graph Convolutional Network with Conditional Random Field.”
    • Journal: Bioinformatics, 36(19), 4918–4927, 2020. [PDF] [Code & Data]
  9. Yahui Long, Min Wu, Yong Liu, Chee-Keong, Kwoh, Jiawei Luo and Xiaoli Li. “Ensembling graph attention networks for human microbe-drug association prediction.”
    • Journal: Published in a special issue in Bioinformatics, 36, i779–i786, 2020. [PDF] [Code & Data]
    • Conference: Accepted by Proceedings of the 19th European Conference on Computational Biology (ECCB 2020). [Acceptance rate: 21.18%]
  10. Yahui Long, Jiawei Luo, Yu Zhang and Yan Xia. “Predicting Human Microbe-Disease Associations via Graph Attention Networks with Inductive Matrix Completion.”
    • Journal: Accepted by Briefings in Bioinformatics, 2020. [PDF][Code & Data]
  11. Yahui Long and Jiawei Luo. “Association mining to identify microbe drug interactions based on heterogeneous network embedding representation.”
    • Journal: IEEE Journal of Biomedical and Health Informatics (J-BHI), 25(01), 266-275, 2020. [PDF]
  12. Yahui Long, Yu Zhang, Min Wu, Shaoliang Peng, Chee-Keong Kwoh, Jiawei Luo and Xiaoli Li. “Predicting Drugs for COVID-19/SARS-CoV-2 via Heterogeneous Graph Attention Networks.”
    • Journal: To be published in a special issue in Methods, 2021.
    • Conference: Accepted by IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2020). [PDF]
  13. Yu Zhang, Yahui Long, Rui Yin, Chee Keong Kwoh. “DL-CRISPR: A Deep Learning Method for Off-Target Activity Prediction in CRISPR/Cas9 With Data Augmentation.”
    • Journal: IEEE Access, 2020. [PDF]
  14. Yu Zhang, Yahui Long, Chee-Keong, Kwoh. “Deep learning based DNA: RNA triplex forming potential prediction.”
    • Journal: BMC Bioinformatics, 2020. [PDF]
  15. Yahui Long and Jiawei Luo. “WMGHMDA: a novel weighted meta-graph-based model for predicting human microbe-disease association on heterogeneous information network.”
    • Journal: BMC Bioinformatics, 20(01):541, 2019. [PDF]
  16. Jiawei Luo and Yahui Long. “NTSHMDA: Prediction of human microbe-disease association based on random walk by integrating network topological similarity.”
    • Journal: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 17(4), 1341–1351, 2018. [PDF][Code & Data]
  17. Caipin Liu, Yahui Long, Jianxu Mao, Hui Zhang, Ruizhi Huang and Yang Dai. “An effective image fusion algorithm based on grey relation of similarity and morphology.”
    • Journal: Journal of Ambient Intelligence and Humanized Computing, 2018. [PDF]
  18. Caipin Liu, Yahui Long and Jianxu Mao. “Energy-efficient multi-focus image fusion based on neighbor distance and morphology.”
    • Journal: Optik, 127, 11354-11363, 2016. [PDF]