2024-10-09T18:19:07+08:002022-07-08|
聯絡信息
職稱
副教授
辦公室
(辦公室) E12-4013
電話
(辦公室) +853 8822 9121
電郵
ethanpwang@um.edu.mo
諮詢時間

星期二、三 16:00 – 17:00

教學

HSCI4012 Bioinformatics in Action
GEST1002 Quantitative Reasoning for Social Science
HSCI7001 Artificial Intelligence In Medicine

研究團隊
名稱 職稱 辦公室 電話 電郵
陳丹博士生 (實驗室代表)
付恒毅博士生
黎慧君博士生
王若瑤博士生
王悅雯博士生
Education
PhD University of Wisconsin-Madison (Immunology), 2001
MEng Cornell University (Computer Science), 2002
BSc Peking University (Biochemistry & Molecular Biology), 1996

 

Position
2022 – Present Associate Professor, Faculty of Health Sciences, University of Macau
2017 – 2022 Principle Investigator, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, PR China
2011 – 2017 Principle Investigator, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, PR China
2006 – 2011 Research Associate, La Jolla Institute of Allergy & Immunology, La Jolla, CA, USA
2003 – 2006 Postdoctoral Researcher, Computational Systems Biology Laboratory, University of Georgia, Athens, GA, USA
Research Interests
Our research interests are to obtain a quantitative understanding of the dynamics of tumorigenesis, particularly metastasis; and to develop mathematical characterizations of the common principles underlying tumor heterogeneity. We also have a strong translational interest to develop effective therapies for cancer driven by systems biology and data science.

 

Currently our research focuses on three directions. The first direction is computational systems biology of cancer. We are combining computational and systems biology strategies to understand how dynamic and heterogeneous regulatory networks drive metastasis, and to decipher the quantitative rules that dictate how certain combination of mutations could drive tumorigenesis. The second area of active research is cancer data science. Currently we are interested in developing novel algorithms for single-cell omics data analysis, regulatory network inference, and multi-modal omics and clinical data integration. Finally, we are actively pursuing translation research to develop novel biomarkers for early cancer/metastasis detection, and combinatorial therapeutic strategies to overcome drug resistance.
Representative Publications
  1. Wang, W., Yuan, T., Ma, L., Zhu, Y., Bao, J., Zhao, X., Zhao, Y., Zong, Y., Zhang, Y., Yang, S., Qiu X., Shen, S., Wu R., Wu, T., Wang, H. #, Gao, D. #, Wang, P. #, Chen, L. # (2022) Hepatobiliary Tumor Organoids Reveal HLA Class I Neoantigen Landscape and Antitumoral Activity of Neoantigen Peptide Enhanced with Immune Checkpoint Inhibitors. Advanced Science (Weinh)
  2. Liu, Y.W., Xue, M.Z., Cao, Y., Qin, H., Wang, Y., Miao, H., Wang, P. #, Hu, X. #, Shen, J.K. #, Xiong, B.# (2021) Multi-omics characterization of WNT pathway reactivation to ameliorate BET inhibitor resistance in liver cancer cells, Genomics, 113, 1057.
  3. Wang, P., and Chen, L. # (2020) Critical transitions and tipping points in EMT, Quantitative Biology, 1-8.
  4. Jiang, Z., Lu, L., Liu, Y., Zhang, S., Li, S., Wang, G. #, Wang, P. #, and Chen, L. # (2020) SMAD7 and SERPINE1 as novel dynamic network biomarkers to detect and regulate the tipping point of TGF-beta induced EMT. Science Bulletin., 65: 842-853
  5. Liu, Y., Xue, M., Du, S., Feng, W., Zhang, K., Zhang, L., Liu, H., Jia, G., Wu, L., Hu, X. #, Chen, L. #, and Wang, P. # (2019) Competitive endogenous RNA is an intrinsic component of EMT regulatory circuits and modulates EMT, Nature Communications 10, 1637.
  6. Jiang, Y. Z., Ma, D., Suo, C., Shi, J., Xue, M., Hu, X., Xiao, Y., Yu, K. D., Liu, Y. R., Yu, Y., Zheng, Y., Li, X., Zhang, C., Hu, P., Zhang, J., Hua, Q., Zhang, J., Hou, W., Ren, L., Bao, D., Li, B., Yang, J., Yao, L., Zuo, W. J., Zhao, S., Gong, Y., Ren, Y. X., Zhao, Y. X., Yang, Y. S., Niu, Z., Cao, Z. G., Stover, D. G., Verschraegen, C., Kaklamani, V., Daemen, A., Benson, J. R., Takabe, K., Bai, F., Li, D. Q., Wang, P. #, Shi, L. #, Huang, W. #, and Shao, Z. M. # (2019) Genomic and Transcriptomic Landscape of Triple-Negative Breast Cancers: Subtypes and Treatment Strategies, Cancer Cell 35, 428-440 e425.
  7. Xue, M., Liu, H., Zhang, L., Chang, H., Liu, Y., Du, S., Yang, Y., and Wang, P. # (2017) Computational identification of mutually exclusive transcriptional drivers dysregulating metastatic microRNAs in prostate cancer, Nature Communications 8, 14917.
  8. Chang, H., Liu, Y., Xue, M., Liu, H., Du, S., Zhang, L., and Wang, P. # (2016) Synergistic action of master transcription factors controls epithelial-to-mesenchymal transition, Nucleic Acids Research 44, 2514-2527.
  9. Li, L., Wang, D., Xue, M., Mi, X., Liang, Y., and Wang, P. # (2014) 3’UTR shortening identifies high-risk cancers with targeted dysregulation of the ceRNA network, Scientific Reports 4, 5406.
  10. Wang, P., Sidney, J., Kim, Y., Sette, A., Lund, O., Nielsen, M., and Peters, B. (2010) Peptide binding predictions for HLA DR, DP and DQ molecules, BMC Bioinformatics 11, 568.
  11. Wang, P., Sidney, J., Dow, C., Mothe, B., Sette, A., and Peters, B. (2008) A systematic assessment of MHC class II peptide binding predictions and evaluation of a consensus approach, PLoS Computational Biology 4, e1000048.
  12. Wang, P., Morgan, A. A., Zhang, Q., Sette, A., and Peters, B. (2007) Automating document classification for the Immune Epitope Database, BMC Bioinformatics 8, 269.
  13. Wang, P., Yan, B., Guo, J. T., Hicks, C., and Xu, Y. (2005) Structural genomics analysis of alternative splicing and application to isoform structure modeling, The Proceedings of the National Academy of Sciences 102, 18920-18925.
Full Publications List
Research Grants
2018 – 2022 MOST of the People´s Republic of China grant Y82FC51011 (project PI, 2.6 million yuan)
2016 – 2020 NSFC grant 31671380 (PI, 600K yuan)
2013 – 2016 NSFC grant 31271413 (PI, 800K yuan)
2013 – 2015 Hundred Talents Program of Chinese Academy of Sciences (PI, 2.6 million yuan)
11/2012 – 10/2014 Science  and  Technology  Commission  of  Shanghai  Municipality grant 12DZ1910800 (PI, 3.1 million yuan)
Awards
Hundred Talents Program of Chinese Academy of Sciences (2013)