welcome to Department of Biomedical Sciences & Engineering.

Full-Time Faculty

Assistant Professor Hui-Yin Chang

Posted on: 2024-05-16
Research interests: proteomics, metabolomics, bioinformatics, machine learning, data mining
E-mail: dr.chuiyin@gmail.com 
LinkedIn: https://www.linkedin.com/in/chuiyin/?trk=public_profile-settings_edit-profile-content

Ph. D, Biomedical Informatics, National Yang Ming University
MA. Sc, Medical Informatics, National Cheng Kung University
BS, Applied Information Science, Chung Shan Medical University
Work Experiences:

Postdoctoral fellow, Academia Sinica, Taiwan
Postdoctoral fellow, Pathology, University of Michigan

  1. Shuo-Fu Chen, Fu-Chiang Yeh, Ching-Yun Chen, Hui-Yin Chang (2023, Jun). Tailored therapeutic decision of rheumatoid arthritis using proteomic strategies: how to start and when to stop?. Clinical Proteomics, 20(1), 22. nstc 111-2222-E-008-005. [Corresponding Author; SCIE; IF= 3.8]
  2. Hui-Yin Chang, Sarah E. Haynes, Fengchao Yu, and Alexey I. Nesvizhskii (2022, Sep). Implementing the MSFragger Search Engine as a Node in Proteome Discoverer. Journal of Proteome Research. (Accepted). nstc 110-2320-B-008-001-MY2. [First/Co-corresponding Author; SCI; IF= 5.37]
  3. Tianen He, Youqi Liu, Yan Zhou, Lu Li, He Wang, Shanjun Chen, Jinlong Gao, Wenhao Jiang, Yi Yu, Weigang Ge, Hui-Yin Chang, Ziquan Fan, Alexey I. Nesvizhskii, Tiannan Guo, and Yaoting Sun (2022, Oct). Comparative Evaluation of Proteome Discoverer and FragPipe for the TMT-Based Proteome Quantification. Journal of Proteome Research. 2022;21;3007-3015. [SCI; IF= 5.37]
  4. Kun-Lin Wu, Che-Yi Chou, Hui-Yin Chang, Chih-Hsun Wu, An-Lun Li, Chien-Lung Chen, Jen-Chieh Tsai, Yi-Fan Chen, Chiung-Tong Chen, Chin-Chung Tseng, Jin-Bor Chen, I-Kuan Wang, Yu-Juei Hsu, Shih-Hua Lin, Chiu Ching Huang, Nianhan Ma (2022, Sep). Peritoneal effluent MicroRNA profile for detection of encapsulating peritoneal sclerosis. Clinica Chimica Acta, 536 (2022) 45-55. [SCI; IF= 6.314]
  5. Chang, H. Y., Colby, S. M., Du, X., Gomez, J. D., Helf, M. J., Kechris, K., Kirkpatrick, C. R., Li, S., Patti, G. J., Renslow, R. S., Subramaniam, S., Verma, M., Xia, J., Young, J. D. A Practical Guide to Metabolomics Software Development. Anal Chem. 2021;93(4):1912-23. [First Author; SCI; IF=6.042]
  6. Huang, C., Chen, L., Savage, S. R., Eguez, R. V., Dou, Y., Li, Y., da Veiga Leprevost, F., Jaehnig, E. J., Lei, J. T., Wen, B., Schnaubelt, M., Krug, K., Song, X., Cieslik, M., Chang, H. Y., et al., Clinical Proteomic Tumor Analysis. Proteogenomic insights into the biology and treatment of HPV-negative head and neck squamous cell carcinoma. Cancer Cell. 2021;39(3):361-79 e16. [SCI; IF=26.602]
  7. da Veiga Leprevost, F., Haynes, S. E., Avtonomov, D. M., Chang, H. Y. Shanmugam, A. K., Mellacheruvu, D., Kong, A. T., Nesvizhskii, A. I. (2020, Jul). Philosopher: a versatile toolkit for shotgun proteomics data analysis. Nature Methods, 17(9): 869-870. [SCI; IF=30.822]
  8. Chang, H. Y., Kong, A. T., da Veiga Leprevost, F., Avtonomov, D. M., Haynes, S.E. and Nesvizhskii, A. I. (2020, Apr). Crystal-C: A computational tool for refinement of open search results. Journal of Proteome Research, 19(6): 2511-15. [First AuthorSCI; IF=4.074]
  9. Djomehri, S. I., Gonzalez, M. E., da Veiga Leprevost, F., Tekula, S. R., Chang, H. Y., White, M. J., Cimino-Mathews, A., Burman, B., Basrur, V., Argani, P., Nesvizhskii, A. I., Kleer, C. G. (2020, Apr). Quantitative proteomic landscape of metaplastic breast carcinoma pathological subtypes and their relationship to triple-negative tumors. Nature Communications, 11(1): 1723. [SCI; IF=12.121]
  10. Dou, Y., E. A. Kawaler, D. Cui Zhou, M. A. Gritsenko, C. Huang, L. Blumenberg, A. Karpova, V. A. Petyuk, S. R. Savage, S. Satpathy, W. Liu, Y. Wu,C. F. Tsai, B. Wen, Z. Li, S. Cao, J. Moon, Z. Shi, M. Cornwell, M. A. Wyczalkowski, R. K. Chu, S. Vasaikar, H. Zhou, Q. Gao, R. J. Moore, K. Li, S. Sethuraman, M. E. Monroe, R. Zhao, D. Heiman, K. Krug, K. Clauser, R. Kothadia, Y. Maruvka, A. R. Pico, A. E. Oliphant, E. L. Hoskins, S. L. Pugh, S. J. I. Beecroft, D. W. Adams, J. C. Jarman, A. Kong, H. Y. Chang, B. Reva, Y. Liao, D. Rykunov, A. Colaprico, X. S. Chen, A. Czekanski, M. Jedryka, R. Matkowski, M. Wiznerowicz, T. Hiltke, E. Boja, C. R. Kinsinger, M. Mesri, A. I.Robles, H. Rodriguez, D. Mutch, K. Fuh, M. J. Ellis, D. DeLair, M. Thiagarajan, D. R. Mani, G. Getz, M. Noble, A. I. Nesvizhskii, P. Wang, M. L. Anderson, D. A. Levine, R. D. Smith, S. H. Payne, K. V. Ruggles, K. D. Rodland, L. Ding, B. Zhang, T. Liu, D. Fenyo (2020, Feb). Proteogenomic Characterization of Endometrial Carcinoma. Cell, 180(4): 729-748 e726. [SCI; IF=38.637]
  11. Clark, D. J., S. M. Dhanasekaran, F. Petralia, J. Pan, X. Song, Y. Hu, F. da VeigaLeprevost, B. Reva, T. M. Lih, H. Y. Chang, W. Ma, C. Huang, C. J. Ricketts, L. Chen, A. Krek, Y. Li, D. Rykunov, Q. K. Li, L. S. Chen, U. Ozbek, S. Vasaikar, Y. Wu, S. Yoo, S. Chowdhury, M. A. Wyczalkowski, J. Ji, M. Schnaubelt, A. Kong, S. Sethuraman, D. M. Avtonomov, M. Ao, A. Colaprico, S. Cao, K. C. Cho, S. Kalayci, S. Ma, W. Liu, K. Ruggles, A. Calinawan, Z. H. Gumus, D. Geizler, E. Kawaler, G. C. Teo, B. Wen, Y. Zhang, S. Keegan, K. Li, F. Chen, N. Edwards, P. M. Pierorazio, X. S. Chen, C. P. Pavlovich, A. A. Hakimi, G. Brominski, J. J. Hsieh, A. Antczak, T. Omelchenko, J. Lubinski, M. Wiznerowicz, W. M. Linehan, C. R. Kinsinger, M. Thiagarajan, E. S. Boja, M. Mesri, T. Hiltke, A. I. Robles, H. Rodriguez, J. Qian, D. Fenyo, B. Zhang, L. Ding, E. Schadt, A. M. Chinnaiyan, Z. Zhang, G. S. Omenn, M. Cieslik, D. W. Chan, A. I. Nesvizhskii, P. Wang, H. Zhang, et al. (2020, Jan). Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma. Cell, 179(4): 964-983 e931. [SCI; IF=38.637]
  12. H. Y. Chang, C. T. Chen, C. L. Ko, Y. J. Chen, Y. J. Chen, W. L. Hsu, C. G. Juo, and T. Y. Sung (2017, Dec). iTop-Q: an Intelligent Tool for Top-down Proteomics Quantitation Using DYAMOND Algorithm. Analytical Chemistry, 89(24): 13128-13136. [First AuthorSCI; IF=6.042]
  13. Lih, T. M., W. K. Choong, C. C. Chen, C. W. Cheng, H. N. Lin, C. T. Chen, H. Y.Chang, W. L. Hsu, and T. Y. Sung (2016, Jul). MAGIC-web: a platform for untargeted and targeted N-linked glycoprotein identification. Nucleic Acids Research, 44(W1): W575-580. [SCI; IF=10.162]
  14. H. Y. Chang, C. T. Chen, T. M. Lih, K. S. Lynn, C. G. Juo, W. L. Hsu, and T. Y. Sung (2016, Jan). iMet-Q: A User-Friendly Tool for Label-Free Metabolomics Quantitation Using Dynamic Peak-Width Determination. PLoS One, 11(1): e0146112. [First AuthorSCI; IF=2.806]
  15. Choong, W. K., H. Y. Chang, C. T. Chen, C. F. Tsai, W. L. Hsu, Y. J. Chen, and T.Y. Sung (2015, Dec). Informatics View on the Challenges of Identifying Missing Proteins from Shotgun Proteomics. Journal of Proteome Research, 14(12): 5396-5407. [SCI; IF=4.268]
  16. Lynn, K. S., M. L. Cheng, Y. R. Chen, C. Hsu, A. Chen, T. M. Lih, H. Y. Chang, C. J. Huang, M. S. Shiao, W. H. Pan, T. Y. Sung, and W. L. Hsu (2015, Feb). Metabolite identification for mass spectrometry-based metabolomics using multiple types of correlated ion information. Analytical Chemistry, 87(4): 2143-2151. [SCI; IF=5.886]
  1. Jie-Wei Chiu, Hui-Yin Chang (2022, Aug). DeNox: A Visualization Tool for Automatic Signal Extraction from LC-MS/MS Proteomics and Metabolomics Data. The 18th Taiwan Society for Mass Spectrometry annual conference.
  2. Yi-Tien Kuo, Hui-Yin Chang (2022, Mar). A complete workflow for the batch effect elimination of LC-MS/MS data. International Symposium on Evolutionary Genomics and Bioinformatics 2022
  3. Yi-Fan Chen, Hui-Yin Chang (2022, Mar). Afan: an artificial intelligence software for omics da-ta analysis. International Symposium on Evolutionary Genomics and Bioinformatics 2022
  4. Jie-Wei Chiu, Hui-Yin Chang (2022, Mar). DeNox: Automatic Extraction of Metabolite Signals from LC-MS/MS for Quality Contro. International Symposium on Evolutionary Genomics and Bioinformatics 2022
  5. Hui-Yin Chang, Felipe da Veiga Leprevost, Wei-ping Ma, Pei Wang, Bo Wen, Bing Zhang, Alexey I. Nesvizhskii (2020, Jun). TMT-Integrator: An efficient analysis and multi-level report generation for labeling-based proteomics experiments. 68th ASMS Conference on Mass Spectrometry and Allied Topics.
  6. Hui-Yin Chang, Andy T. Kong, Felipe V. Leprevost, Fengchao Yu, Guo Ci Teo, Dmitry M. Avtonomov, Venkatesha Basrur, Alexey I. Nesvizhskii (2019, Jun). Implementation of MSFragger and Philosopher (PeptideProphet) as Proteome Discoverer Nodes. 67th ASMS Conference on Mass Spectrometry and Allied Topics. 
  7. Hui-Yin Chang, Andy T. Kong, Felipe V. Leprevost, Dmitry M. Avtonomov, Alexey I. Nesvizhskii (2018, Jun). Crystal-C: A computational tool for refinement of open search results. 66th ASMS Conference on Mass Spectrometryand Allied Topics. 
  8. Hui-Yin Chang, Ching-Tai Chen, Chiun-Gung Juo, Wen-Lian Hsu, Ting-Yi Sung(2016, Sep). iTop-Q: an intelligent top-down proteomics quantification tool using the DYAMOND algorithm for charge state deconvolution. HUPO 15th Annual World Congress.
Last Updated: 2024-05-24