Project Technical Assistant Research Fellow
Paul Wei-Che Hsu
09/2004- 03/2009 Ph.D., Institute of Bioinformatics, National Chiao Tung University.
09/1996- 06/1998 M.S., Institute of Biology, Tunghai University
09/1992- 06/1996 B.S., Department of Biology, Tunghai University
01/2016- 04/2020 Bioinformatics Core Facility Manager, Associate Research Specialist, Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan.
06/2009- 12/2015 Bioinformatics Core Facility Manager, Assistant Research Specialist, Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan.
02/2007- 03/2008 Invited Researcher, French National Centre for Scientific Research (CNRS) FRE 3235, France.
02/2003- 08/2004 Medical Big Data Analyst, Bioinformatics Division, Vita Genomics Inc., Taiwan.
12/2000- 01/2003 Chief Software Architect, Bioinformatics Group, U-Vision Biotech Inc., Taiwan.
09/1998- 06/2000 Information Management, Armed Forces Medical Supplies Office (military service), Taiwan.
1. Multiomics Analysis and Precision Medicine:
Multiomics analysis is an interdisciplinary field that combines biology and data science. It aims to comprehensively analyze various levels of human biological data, including the genome, transcriptome, proteome, and metabolome. By integrating multiomics analysis, we can gain a holistic understanding of human biology, enabling precision medicine. This research focuses on utilizing multiomics analysis methods to investigate disease mechanisms based on individual variations and provide personalized prevention, diagnosis, and treatment strategies.
2. Artificial Intelligence and Disease Prediction:
Artificial intelligence (AI) has emerged as a powerful tool for disease prediction. This research aims to leverage AI techniques in analyzing large-scale clinical data to predict disease occurrence and progression.
3. Gene Regulatory Network Analysis:
Gene regulatory networks play a vital role in understanding biological processes and diseases. This research focuses on analyzing gene regulatory networks using advanced bioinformatics approaches to unravel the complex interactions and regulatory relationships among genes.
4. Development of Bioinformatics Analysis Methods:
Currently, nine types of bioinformatics methods (Figure 1) are primarily utilized in the biological laboratory, including genomics, transcriptomics, proteomics, metabolomics, and more. These methods are applied in various biological data analyses, revealing essential information regarding gene functions, disease mechanisms, and precision medicine. In addition to developing bioinformatics analysis methods, we will create open-source bioinformatics tools to facilitate collaboration and knowledge sharing among researchers. This will accelerate the progress of biomedical research and promote the realization of precision medicine.
Figure 1: Different types of bioinformatics methods
HONORS & AWARDS
06/2006 Scholarship from the Ministry of Education (Elite Study Abroad Project), Taiwan.
10/2006 Best presentation award, National Chiao Tung University, 2006 Annual Biology Research Poster Contest.
08/2021-current Machine learning and integrative analysis of multi-omics data
National Health Institute Taiwan Precision Medicine Talent Training Program
11/2009-12/2018 Bioinformatics section of experimental approaches in molecular and cell biology. The Taiwan International Graduate Program in “Molecular and Cell Biology”, TIGP-MCB.
09/2011-current Bioinformatics training course section. Academia Sinica Life Science Library, LSL.
02/2016-05/2020 Next-generation sequencing course. Graduate Institute of Medical Genomics and Proteomics, National Taiwan University, NTUCM.
- Lu, S.H., Wu, Y.H., Su, L.Y., Hsu, Z.T., Weng, T.H., Wang, H.Y., Yu, C., Hsu, P.W. and Tsai, S. Y. (2023). Cardiac myofibrillogenesis is spatiotemporally modulated by the molecular chaperone UNC45B. Stem Cell Reports. S2213-6711(23)00184-4.
- Hsu, P.W., Liao, P.C., Kao, Y.H., Lin, X.Y., Chien, R.N., Yeh, C.T., Lai, C.C., Shyu, Y.C., Lin, C.L. (2022). The Mutation Hotspots at UGT1A Locus May Be Associated with Gilbert’s Syndrome Affecting the Taiwanese Population. International Journal of Molecular Sciences. 23(20):12709.
- Wu, I.W., Tsai, T.H., Lo, C.J., Chou, Y.J., Yeh, C.H., Chan, Y.H., Chen, J.H., Hsu, P.W., Pan, H.C., Hsu, H.J., Chen, C.Y., Lee, C.C., Shyu, Y.C., Lin, C.L., Cheng, M.L., Lai, C.C., Sytwu, H.K., Tsai, T.F. (2022). npj Digital Medicine. 5(1):166.
- Shyu, Y.C., Liao, P.C., Huang, T.S., Yang, C.J., Lu, M.J., Huang, S.M., Lin, X.Y., Liou, C.C., Kao, Y.H., Lu, C.H., Peng, H.L., Chen, J.R., Cherng, W.J., Yang, N.I., Chen, Y.C., Pan, H.C., Jiang, S.T., Hsu, C.C., Lin, G., Yuan, S.S., Hsu, P.W., Wu, K.J., Lee, T.L., Shen, C.J.(2022). Advanced Science. 9(25):e2201409.
- Lu, S.H., Lee, K.Z., Hsu, P.W., Su, L.Y., Yeh, Y.C., Pan, C.Y., Tsai, S.Y. (2022). Alternative Splicing Mediated by RNA-Binding Protein RBM24 Facilitates Cardiac Myofibrillogenesis in a Differentiation Stage-Specific Manner. Circulation Research. 30(1):112-129.
- Yeh, C.W., Huang, W.C., Hsu, P.H., Yeh KH, Wang, L.C., Hsu, P.W., Lin, H.C., Chen, Y.N., Chen, S.C., Yeang, C.H., Yen, H.S. (2021). The C-degron pathway eliminates mislocalized proteins and products of deubiquitinating enzymes. EMBO 40(7):e105846.
- Emanuele, M.J., Elia, A.E., Xu, Q., Thoma, C.R., Izhar, L., Leng, Y., Guo, A., Chen, Y.N., Rush, J., Hsu, P.W., et al. (2011). Global Identification of Modular Cullin-RING Ligase Substrates. Cell 147, 459-474.
- Tsai, W.C. †, Hsu, P.W. †, Lai, T.C., Chau, G.Y., Lin, C.W., Chen, C.M., Lin, C.D., Liao, Y.L., Wang, J.L., Chau, Y.P., et al. (2009). MicroRNA-122, a tumor suppressor microRNA that regulates intrahepatic metastasis of hepatocellular carcinoma. Hepatology 49, 1571-1582. († First author).
- Hsu, P.W., Lin, L.Z., Hsu, S.D., Hsu, J.B., and Huang, H.D. (2007). ViTa: prediction of host microRNAs targets on viruses. Nucleic acids research 35, D381-385.
- Hsu, P.W., Huang, H.D., Hsu, S.D., Lin, L.Z., Tsou, A.P., Tseng, C.P., Stadler, P.F., Washietl, S., and Hofacker, I.L. (2006). miRNAMap: genomic maps of microRNA genes and their target genes in mammalian genomes. Nucleic acids research 34, D135-139.