Fengchao Yu

Department of Electronic and Computer Engineering · The Hong Kong University of Science and Technology · Kowloon · Hong Kong S.A.R.

I am a post-doc from The Hong Kong University of Science and Technology (HKUST). I got my PhD from HKUST. My research interests include proteomics, computational biology, machine learning, and statistics. In the past few years, I addressed the computational issue in the cross-linked peptides identification and proposed a coding-based framework to identify post-translational modification (PTM) with an unlimited and unbiased manner. Right now, I continue my study on the PTM identification since there are unaddressed issues.

Research Experience

Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology

Post-Doctoral Fellow


  1. Studying acetylproteomics using a quantitative based approach.
  2. To be continued...

July 2017 - Present

Division of Biomedical Engineering, The Hong Kong University of Science and Technology

Doctor of Philosophy in Bioengineering


  1. Developed methods to identify cross-linked peptides fast (i.e., linear computational complexity) and precisely.
  2. Developed methods to identify post-translational modifications (PTMs) in an unlimited and unbiased manner.

September 2012 - May 2017

Department of Optical Engineering, Zhejiang University

Master in Optical Engineering

PTM Image Reconstruction:

  1. Developed methods to reconstruct positron emission tomography (PET) image based on the state-space model.
  2. Accelerated the PEM image reconstruction algorithm using GPU-based parallel computing (i.e., CUDA).

September 2009 - March 2012



  1. Dai, J.*, Yu, F.*, & Yu, W. (2018). Understanding the limit of open search in the identification of peptides with post-translational modifications — A simulation-based study. Bioinformatics, under review. (* co-first author) (bioRxiv pre-print)
  2. Liu, S.*, Yu, F.*, Hu, Q., Wang, T., Yu, L., Du, S., Yu, W., & Li, N. (2018). Development of in planta chemical cross-linking-based quantitative interactomics in Arabidopsis. Journal of Proteome Research, in-press. (* co-first author)
  3. Dai, J.*, Jiang, W.*, Yu, F.*, & Yu, W. (2018). Xolik: finding cross-linked peptides with maximum paired scores in linear time. Bioinformatics, in-press. (* co-first author)
  4. Liu, S.*, Yu, F.*, Yang, Z., Wang, T., Xiong, H., Chang, C., Yu, W., & Li, N. (2018). Establishment of dimethyl labeling-based quantitative acetylproteomics in Arabidopsis. Molecular & Cellular Proteomics, 17(5), 1010-1027. (* co-first author)
  5. Yu, F., Li, N., & Yu, W. (2017). Exhaustively Identifying Cross-Linked Peptides with a Linear Computational Complexity. Journal of Proteome Research, 16(10), 3942-3952.
  6. Yu, F., Li, N., & Yu, W. (2016). PIPI: PTM-Invariant Peptide Identification Using Coding Method. Journal of Proteome Research, 15(12), 4423-4435.
  7. Yu, F., Li, N., & Yu, W. (2016). ECL: an exhaustive search tool for the identification of cross-linked peptides using whole database. BMC Boinformatics, 17(1), 217.
  8. Zhu, X.*, Yu, F.*, Yang, Z., Liu, S., Dai, C., Lu, X., Liu, C., Yu, W., & Li, N. (2016). In planta chemical cross‐linking and mass spectrometry analysis of protein structure and interaction in Arabidopsis. Proteomics, 16(13), pp.1915-1927. (* co-first author)

PET Image Reconstruction

  1. Yu, F., Liu, H., Hu, Z., & Shi, P. (2012). Graphics processing unit (GPU)-accelerated particle filter framework for positron emission tomography image reconstruction. JOSA A, 29(4), 637-643.
  2. Yu, F., Liu, H., & Shi, P. (2012, January). Pet image reconstruction based on particle filter framework. In Biomedical and Health Informatics (BHI), 2012 IEEE-EMBS International Conference on (pp. 851-853). IEEE.
  3. Yu, F., Liu, H., & Shi, P. (2011, September). PET image reconstruction: GPU-accelerated particle filter framework. In Image Processing (ICIP), 2011 18th IEEE International Conference on (pp. 417-420). IEEE.

Patents (Chinese)

  1. 刘华峰,余风潮。“一种基于粒子滤波的静态PET图像重建方法。” 中国专利:102184559A,公开日期:2011年9月14日。
  2. 刘华峰,余风潮。“一种基于GPU多核并行处理的PET图像重建方法。” 中国专利:102831627A,公开日期:2012年12月19日。


  • UGC Research Travel Grant Award (2017-18)
  • UGC Research Travel Grant Award (2016-17)
  • Graduate Student Research Award Program of HKMHDIA (Hong Kong Medical & Healthcare Device Industries Association Limited) (2015-16)
  • Graduate Student Second-Class Honor (2011)
  • Excellent Bachelor Thesis(2009)
  • Third-Class Scholarship (2008)
  • Third-Class Scholarship (2007)
  • Third-Class Scholarship (2006)


Programming Languages