曾远松（19级）

曾远松

简历

  • 2023- 重庆大学 弘深青年教师
  • 2019-2023 中山大学 计算机学院 博士
  • 2018-2019 深信服科技股份有限公司 工程师
  • 2015-2018 重庆大学 计算机科学与技术 硕士
  • 2013-2015 华中科技大学 计算机科学与技术(辅修) 学士
  • 2011–2015 武汉理工大学 教育技术学 学士

Publications

  1. Y Zeng, M Luo, N Shangguan, P Shi, J Feng, J Xu, K Chen, Y Lu, W Yu, and Yuedong Yang*. Deciphering Cell Types by Integrating scATAC-seq Data with Genome Sequences Nature Computational Science 2024;4:285–298.
  2. Zeng Y, Z Wei, Q Yuan, S Chen, W Yu, Y Lu, J Gao, Y Yang. Identifying B-cell epitopes using AlphaFold2 predicted structures and pretrained language model. Bioinformatics 2023;btad187.
  3. Zeng Y, Yin R, Luo M, Chen J, Pan Z, Lu Y, Yu W, Yuedong Yang*. Identifying Spatial Domain by Adapting Transcriptomics with Histology through Contrastive Learning. Brief Bioinfo 2023; bbad048.
  4. Zeng Y, Zhuoyi Wei, Weijiang Yu, Rui Yin, Bingling Li, Zhonghui Tang, Yutong Lu, Yuedong Yang*. Spatial Transcriptomics Prediction from Histology jointly through Transformer and Graph Neural Networks. Brief Bioinfo 2022. doi: https://doi.org/10.1101/2022.04.25.489397.
  5. Zeng Y, Wei Z, Zhong F, Pan Z, Lu Y, Yuedong Yang*. A Parameter-free Deep Embedded Clustering Method for Single-cell RNA-seq Data. Brief Bioinfo 2022.
  6. Zeng Y, Zhou X, Pan Z, Lu Y*, Yuedong Yang*. A Robust and Scalable Graph Neural Network for Accurate Single Cell Classification. Brief in Bioinfo 2022; bbab570.
  7. Zeng Y, Zhou X, Rao J, Lu Y*, Yuedong Yang*. Accurately Clustering Single-cell RNA-seq data by Capturing Structural Relations between Cells through Graph Convolutional Network. BIBM 2020;519-522.
  8. Pan Z, Lin Y, Zhang H, Zeng Y, Yu W, and Yuedong Yang*. A Meta-learning based Graph-Hierarchical Clustering Method for Single Cell RNA-Seq Data. BIBM 2022.
  9. Zhong F, Zeng Y, Liu Y, and Yuedong Yang*. SCdenoise: a reference-based scRNA-seq denoising method using semi-supervised learning. BIBM 2022.
  10. Zhou X, Chai H, Zeng Y, Zhao H, Yuedong Yang*. scAdapt: Virtual adversarial domain adaptation network for single cell RNA-seq data classification across platforms and species. Brief in Bioinfo 2021, bbab281 & RECOMB 2021 (Bioinformatics Top conference).