Fengchao Yu

Research Experience

Journal Publications

1. Polasky, D., Geiszler, D., Yu, F., Li, K., Teo, G. C., & Nesvizhskii, A. I., (2023). MSFragger-Labile: A Flexible Method to Improve Labile PTM Analysis in Proteomics. Molecular & Cellular Proteomics, 100538.
2. Park, J., Yu, F., Fulcher, J.M., Williams, S.M., Engbrecht, K., Moore, R.J., Clair, G.C., Petyuk, V., Nesvizhskii, A.I., & Zhu, Y., (2023). Evaluating Linear Ion Trap for MS3-Based Multiplexed Single-Cell Proteomics. Analytical Chemistry, 95(3), 1888-1898.
3. Dai, S., Liu, S., Zhou, C., Yu, F., Zhu, G., Zhang, W., Deng, H., Burlingame, A., Yu, W., Wang, T., Li, N., (2023). Capturing the Hierarchically Assorted Modules of Protein-protein Interaction in the Organized Nucleome. Molecular Plant, 16(5), 930-961.
4. Chang, H.-Y., Haynes, S. E., Yu, F., & Nesvizhskii, A. I., (2022). Implementing the MSFragger Search Engine as a Node in Proteome Discoverer. Journal of Proteome Research, 22(2), 520-525.
5. Ploasky, D., Yu, F., Geislzer, D., Kai, L., & Nesvizhskii, A. I., (2022). Enabling Large-scale Glycoproteomics Data Analysis with the MSFragger Glyco Software Suite. GLYCOBIOLOGY, 32(11), 973-974.
6. Kacen, A., Javitt, A., Kramer, M., Morgenstern, D., Tsaban, T., Shmueli, M., Teo, G. C., Leprevost, F. V., Barnea, E., Yu, F., Admon, A., Eisenbach, L., Samuels, Y., Schueler-Furman, O., Levin, Y., & Nesvizhskii, A. (2022). Post-translational modifications reshape the antigenic landscape of MHC I-immunopeptidome in tumors. Nature Biotechnology, 41(2), 239-251.
7. Demichev, V., Szyrwiel, L., Yu, F., Teo, G. C., Rosenberger, G., Niewienda, A., Ludwig, D., Decker, J., Kaspar-Schoenefeld, S., Lilley, K., Mulleder, M., Nesvizhskii, A., & Ralser, M. (2022). dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts. Nature Communications, 13, 3944.
8. Desai, H., Yan, T., Yu, F., Sun, A., Villanueva, M., Nesvizhskii, A., & Backus, K. (2022). SP3-enabled Rapid and High Coverage Chemoproteomic Identification of Cell-State Dependent Redox-Sensitive Cysteines. Molecular & Cellular Proteomics, 21(4), 100218.
9. Polasky, D., Geiszler, D., Yu, F. & Nesvizhskii, A. (2022). Multi-attribute Glycan Identification and FDR Control for Glycoproteomics. Molecular & Cellular Proteomics, 21(3), 100205.
10. Moradi, A., Dai, S., Wong, E.O.Y., Zhu, G., Yu, F., Lam, H.M., Wang, Z., Burlingame, A., Lin, C., Afsharifar, A. & Yu, W. (2021). Isotopically Dimethyl Labeling-Based Quantitative Proteomic Analysis of Phosphoproteomes of Soybean Cultivars. Biomolecules, 11(8), p.1218.
11. Petyuk, V.A., Yu, L., Olson, H.M., Yu, F., Clair, G., Qian, W.J., Shulman, J.M. & Bennett, D.A. (2021). Proteomic Profiling of the Substantia Nigra to Identify Determinants of Lewy Body Pathology and Dopaminergic Neuronal Loss. Journal of Proteome Research, 20(5), 2266-2282.
12. Yu, F., Haynes, S., & Nesvizhskii, A. (2021). IonQuant enables accurate and sensitive label-free quantification with FDR-controlled match-between-runs. Molecular & Cellular Proteomics, 20, 100077.
13. Huang, C., Chen, L., Savage, S. R., Eguez, R. V., Dou, Y., Li, Y., ... & Piehowski, P. D. (2021). Proteogenomic insights into the biology and treatment of HPV-negative head and neck squamous cell carcinoma. Cancer Cell, 39(3), 361-379.
14. Geiszler, D., Kong, A., Avtonomov, D., Yu, F., Leprevost, F., & Nesvizhskii, A. (2021). PTM-Shepherd: analysis and summarization of post-translational and chemical modifications from open search results. Molecular & Cellular Proteomics, 20, 100018.
15. Dai, J.*, Yu, F.*, Chen Zhou, & Yu, W. (2021). Understanding the limit of open search in the identification of peptides with post-translational modifications — A simulation-based study. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 18(6), 2884-2890. (* co-first author)
16. Teo, G. C., Polasky, D., Yu, F., & Nesvizhskii, A. (2020). Fast deisotoping algorithm and its implementation in the MSFragger search engine. Journal of Proteome Research, 20(1), 498-505.
17. Polasky, D., Yu, F., Teo, G. C., & Nesvizhskii, A. (2020). Fast and comprehensive N- and O-glycoproteomics analysis with MSFragger-Glyco. Nature Methods, 17(11), 1125–1132.
18. Yu, F., Teo, G. C., Kong, A., Avtonomov, D., Geiszler, D., & Nesvizhskii, A. (2020). Identification of modified peptides using localization-aware open search. Nature Communications, 11, 4065.
19. Yu, F.*, Haynes, S.*, Teo, G. C., Avtonomov, D., Polasky, D., & Nesvizhskii, A. (2020). Fast quantitative analysis of timsTOF PASEF data with MSFragger and IonQuant. Molecular & Cellular Proteomics, 19(9), 1575-1585. (* co-first author)
20. 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, 17(9), 3195-3213. (* co-first author)
21. Dai, J.*, Jiang, W.*, Yu, F.*, & Yu, W. (2018). Xolik: finding cross-linked peptides with maximum paired scores in linear time. Bioinformatics, 35(2), 251-257. (* co-first author)
22. 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)
23. 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.
24. Yu, F., Li, N., & Yu, W. (2016). PIPI: PTM-invariant peptide identification using coding method. Journal of Proteome Research, 15(12), 4423-4435.
25. 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.
26. 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), 1915-1927. (* co-first author)
27. 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.

Presentations

1. Yu, F., Li, K., Yang, K., Polasky, D., & Nesvizhskii, A. (2023, March). Comprehensive single-cell proteomics data analysis using FragPipe. 19th Annual US HUPO Conference (US HUPO 2023). (oral presentation).
2. Vitek, O., Kohler, D., Nesvizhskii, A., & Yu, F. (2023, March). Short Course: Design and Analysis of Quantitative Proteomics Experiments with TMT Labeling: case studies using FragPipe and MSstatsTMT. 19th Annual US HUPO Conference (US HUPO 2023). (short course).
3. Yu, F., Teo, G.C., da Veiga Leprevost, F., Polasky, D., Geiszler, D., Yang, K., Li, K., & Nesvizhskii, A. (2022, October). FragPipe enables one-stop data analysis for bottom-up proteomics. 2022 CASMS virtual conference (CASMS 2022). (poster presentation, best poster award).
4. Yu, F., Teo, G.C., Avtonomov. D., Haynes, S., da Veiga Leprevost, F., Geiszler, D., Polasky, D., Yang, K., & Nesvizhskii, A. (2022, July). FragPipe in headless mode enables seamlessly analyzing LC-MS data in Galaxy platform. 2022 Galaxy Community Conference (GCC 2022). (oral presentation).
5. Yu, F., Kong, A., Patil, S., Avtonomov, D., & Nesvizhskii, A. (2022, June). Pepcentric enables fast peptide searching against public data repositories. 70th ASMS Conference on Mass Spectrometry and Allied Topics (ASMS 2022). (poster presentation).
6. Yu, F., Yang, K., Demichev, V., Haynes, S., Ralser, M., & Nesvizhskii, A. (2022, March). One-stop DIA data analysis using MSFragger-DIA coupled with FragPipe. 18th Annual US HUPO Conference (US HUPO 2022). (poster presentation).
7. Yu, F., Teo, G. C., Haynes, S., Li, G. X., & Nesvizhskii, A. (2021, November). Direct peptide identification from DIA data with MSFragger DIA. 69th ASMS Conference on Mass Spectrometry and Allied Topics (ASMS 2021). (oral presentation).
8. Yu, F., Haynes, S., & Nesvizhskii, A. (2021, March). False discovery rate-controlled match-between-runs enables accurate and sensitive label free quantification. 17th Annual US HUPO Conference (US HUPO 2021). (poster presentation), virtual conference.
9. Yu, F., Teo, G. C., Kong, A., Haynes, S., Avtonomov, D., Geiszler, D., & Nesvizhskii, A. (2020, June). Improved identification of modified peptides using localization-aware open search. 28th Conference on Intelligent Systems for Molecular Biology (ISMB 2020). (poster presentation), virtual conference.
10. Yu, F., Haynes, S., Avtonomov, D., Kong, A., Leprevost, F., & Nesvizhskii, A. (2020, June). Breaking the logjam: fast peptide identification and quantification in timsTOF PASEF data. 68th ASMS Conference on Mass Spectrometry and Allied Topics (ASMS 2020). (poster presentation), virtual conference.
11. Yu, F., Haynes, S., Teo, G. C., Kong, A., Avtonomov, D., Leprevost, F., Chang, H.-Y., Geiszler, D., Polasky, D., & Nesvizhskii, A. (2020, March). Fast and quantitative analysis of timsTOF PASEF data with MSFragger and IonQuant. 16th Annual US HUPO Conference (US HUPO 2020). (poster presentation), virtual conference.
12. Yu, F., Teo, G. C., Kong, A., Leprevost, F., Avtonomov, D., Chang, H., Geiszler, D., Haynes, S., Polasky, D., & Nesvizhskii, A. (2019, October). MSFragger: fast and sensitive peptide identification in diverse proteomic datasets. 18th Human Proteome Organization World Congress (HUPO 2019). (poster presentation), Adelaide, Australia.
13. Yu, F., Teo, G. C., Kong, A., Leprevost, F., Chang, H., & Nesvizhskii, A. (2019, June). Comparison of open search tools. 67th ASMS Conference on Mass Spectrometry and Allied Topics (ASMS 2019). (poster presentation), Atlanta, Georgia.
14. Yu, F., Li, N., & Yu, W. (2018, August). PTM-invariant peptide identification. 5th China Workshop on Computational Proteomics (CNCP 2018). (oral presentation), Beijing, China.
15. Yu, F., Li, N., & Yu, W. (2017, August). PIPI: PTM-invariant peptide identification using coding method. Post-translational Modification Networks, Gordon Research Conference. (poster presentation), Hong Kong, China.
16. Yu, F., Li, N., & Yu, W. (2017, August). PIPI: PTM-invariant peptide identification using coding method. 11th International Conference on Computational Systems Biology (ISB 2017). (oral presentation), Shenzhen, China.
17. Yu, F., Li, N., & Yu, W. (2017, May). Exhaustively identifying cross-linked peptides with a linear complexity. 21st Annual International Conference on Research in Computational Molecular Biology (RECOMB 2017). (poster presentation), Hong Kong, China.
18. 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.
19. 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.

Awards

• CASMS (Chinese American Society for Mass Spectrometry) Best Poster Award (2022)
• US HUPO (United States Human Proteome Organization) Travel Stipend Award (2020)
• UGC Research Travel Grant Award (2018-19)
• UGC Research Travel Grant Award (2018-19)
• 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)

Professional Activities

Journal reviewer