Projects per year
Personal profile
Chinese Name
Biography
Dr. Qianyuan Tang is currently an Assistant Professor in the Department of Physics at Hong Kong Baptist University. He received his Ph.D. in Physics, with a specialization in biophysics, from Nanjing University in 2017. After completing his doctoral studies, Dr. Tang worked as a postdoctoral researcher at the Department of Physics, Hong Kong Baptist University. He then moved to Japan to work as a postdoctoral researcher at the University of Tokyo from November 2017 to March 2021, and later as a Research Scientist at the RIKEN Center for Brain Sciences from April 2021 to January 2023.
Dr. Tang's research leverages advanced computational and data-driven approaches to simplify complex biological systems and uncover the universal laws governing their behaviours. His interdisciplinary research program draws on computational, statistical, and mathematical techniques to analyze complex biological data. By utilizing large datasets and AI-based methods, Dr. Tang aims to better understand the underlying mechanisms of diseases and develop new treatments to improve human health.
Research Interests
1. Data-driven studies of complex systems
2. AI for biomedical sciences
3. Protein evolution and dynamics
4. Complexity and criticality of biological systems
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
PhD, Nanjing University
1 Sept 2011 → 21 Mar 2017
Award Date: 21 Mar 2017
Bachelor, Nanjing University
1 Sept 2007 → 30 Jun 2011
Award Date: 30 Jun 2011
External positions
RIKEN Center for Brain Science
1 Apr 2021 → 31 Jan 2023
University of Tokyo
3 Nov 2017 → 31 Mar 2021
Keywords
- QC Physics
- Statistical Physics
- Complex Systems
- Molecular Biophysics
- Brain Sciences
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Collaborations and top research areas from the last five years
Projects
- 2 Not started
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Protein Reverse Engineering Based on Evolutionary Information
1/01/24 → 31/12/26
Project: Research project
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Research Output
- 8 Journal article
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The Statistical Trends of Protein Evolution: A Lesson from AlphaFold Database
Tang, Q. Y., Ren, W., Wang, J. & Kaneko, K., Oct 2022, In: Molecular Biology and Evolution. 39, 10, 13 p., msac197.Research output: Contribution to journal › Journal article › peer-review
Open Access5 Citations (Scopus) -
Dynamics-Evolution Correspondence in Protein Structures
Tang, Q. Y. & Kaneko, K., 27 Aug 2021, In: Physical Review Letters. 127, 9, 8 p., 098103.Research output: Contribution to journal › Journal article › peer-review
Open Access15 Citations (Scopus) -
Harnessing peak transmission around symptom onset for non-pharmaceutical intervention and containment of the COVID-19 pandemic
Tian, L., Li, X., Qi, F., Tang, Q. Y., Tang, V., Liu, J., Li, Z., Cheng, X., Li, X., Shi, Y., Liu, H. & Tang, L. H., 19 Feb 2021, In: Nature Communications. 12, 1, 12 p., 1147.Research output: Contribution to journal › Journal article › peer-review
Open Access22 Citations (Scopus) -
Functional sensitivity and mutational robustness of proteins
Tang, Q. Y., Hatakeyama, T. S. & Kaneko, K., Sept 2020, In: Physical Review Research. 2, 3, 10 p., 033452.Research output: Contribution to journal › Journal article › peer-review
Open Access6 Citations (Scopus) -
Long-range correlation in protein dynamics: Confirmation by structural data and normal mode analysis
Tang, Q. Y. & Kaneko, K., 13 Feb 2020, In: PLoS Computational Biology. 16, 2, 17 p., e1007670.Research output: Contribution to journal › Journal article › peer-review
Open Access22 Citations (Scopus)