Prof CAO Qin Cara - School of Biomedical Sciences, CUHK

Prof CAO Qin Cara

Research Assistant Professor

39436805

qcao@cuhk.edu.hk

522A, Lo Kwee-Seong Integrated Biomedical Sciences Building, Area 39, CUHK

Publons

ORCID

Biography

Prof. CAO Qin (曹沁) completed her B.Eng. in Computer Science and Technology from Wuhan University, and her Ph.D. in Computer Science and Engineering (CSE) from The Chinese University of Hong Kong (CUHK). She then continued her postdoctoral research at School of Biomedical Sciences (SBS) and CSE in CUHK for three years and became a Research Assistant Professor in 2020. Her research areas are Bioinformatics and Computational Biology. Prof. Cao has received awards including Young Scholars Thesis Award from CUHK, Young Scientist Award 2nd Runner-up from Hong Kong Institution of Science, and Top-10 paper in 2016-17 at RECOMB/ISCB Regulatory Systems Genomics. She has been a (co-)first or (co-)corresponding author of papers in international journals, including Nature Genetics, Nature Machine Intelligence, Genome Biology, Genome Medicine, and Briefings in Bioinformatics.

Research Interests

Reconstruction of gene regulatory networks.
Analysis of multi-omics data and 3D genome structures.
Development of artificial intelligence-driven bioinformatics algorithms and tools.

Selected Publications

1. Wong B.S.H., Kim J.M., Fung S.H., Xiong Q., Ao K.F.K., Wei J., Wang R., Wang D.M., Zhou J., Feng B., Cheng A.S.L., Yip K.Y.#, Tsui S.K.W.#, and Cao Q.#. Driving Accurate Allergen Prediction with Protein Language Models and Generalization-Focused Evaluation. arXiv.

2. Fung S.H., Zhang Z., Wang R., Miao C., Wong B.S.H., Li K.Y., Hong C., Zhou J., Yip K.Y.#, Tsui S.K.W.#, and Cao Q.#. Can Large Language Models “Read” Biological Sequences? A Systematic Evaluation of In-Context Learning for Antibody Characterization. bioRxiv.

3. Li Q., Li K.Y., Nicoletti C., Tsui S.K.W., Puri P.L., Cao Q.#, and Yip K.Y.#. Overcoming Artificial Structures in Resolution-Enhanced Hi-C Data by Signal Decomposition and Multi-Scale Attention. bioRxiv.

4. Chow S.H.C., Shi C.H., Deshpande A., Cao Q., and Yip K.Y. Towards Universal Modeling of Transcript Isoform Expression Levels. bioRxiv.

5. Liao T., Chen S., Wang S., Huang Y., Tsui S.K.W., Stüeken E.E., Cao Q., and Luo H. (2026) Noncanonical genetic markers resolve the pre-GOE emergence of aerobic bacteria in Earth’s history. Proceedings of the National Academy of Sciences 123(4): e2515709123.

6. Miao C.*, Zhang Z.*, Chen J.*, Rebibo D., Wu H., Fung S.H., Cheng A.S.L., Tsui S.K.W., Sinha S., Cao Q.#, and Yip K.Y.#. (2025) Developing foundations for biomedical knowledgebases from literature using large language models – A systematic assessment. Computational and Structural Biotechnology Journal 27(1): 3299-3306.

7. Li K.Y., Cao Q., Chow S.H., Nicoletti C., Puri P.L., Wang H., Leung D., and Yip K.Y.. (2025) Regulatory roles of three-dimensional structures of chromatin domains. Genome Biology 26(1):184.

8. Wang R., Qian Y., Guo X., Song F., Xiong Z., Cai S., Bian X., Wong M.H., Cao Q.#, Cheng L.#, Lu G.#, and Leung K.S.#. (2025) STModule: identifying tissue modules to uncover spatial components and characteristics of transcriptomic landscapes. Genome Medicine 17(1):18.

9. Chen W.*, Miao C.*, Zhang Z., Fung C.S.H., Wang R., Chen Y., Qian Y., Cheng L., Yip KY#, Tsui SKW#, and Cao Q#. (2024) Commonly used software tools produce conflicting and overly-optimistic AUPRC values. Genome Biology 25(1):118.

10. Hong C.*, Cao Q.*#, Zhang Z., Tsui S.K.W., and Yip K.Y.#. (2022) Reusability report: Capturing properties of biological objects and their relationships using graph neural networks. Nature Machine Intelligence 4: 222-226.

11. Qian Y.*, Zhai E.*, Chen S.*, Liu Y., Ma Y., Chen J., Liu J., Qin C., Cao Q.#, Chen J.#, and Cai S.#. (2022) Single-cell RNA-seq dissecting heterogeneity of tumor cells and comprehensive dynamics in tumor microenvironment during lymph nodes metastasis in gastric cancer. International Journal of Cancer 151(8): 1367-1381.

12. Cao Q.*, Zhang Z.*, Fu A.X., Wu Q., Lee T.L., Lo E., Cheng A.S.L., Cheng C., Leung D., and Yip K.Y. (2020) A unified framework for integrative study of heterogeneous gene regulatory mechanisms. Nature Machine Intelligence 2(8): 447-456.

13. Ho E.Y.K.*, Cao Q.*, Gu M., Chan R.W.L., Wu Q., Gerstein M., and Yip K.Y. (2020) Shaping the nebulous enhancer in the era of high-throughput assays and genome editing. Briefings in Bioinformatics 21(3): 836-850.

14. Cao Q., Anyansi C., Hu X., Xu L., Xiong L., Tang W., Mok M.T.S., Cheng C., Fan X., Gerstein M, Cheng ASL, and Yip KY. (2017) Reconstruction of enhancer–target networks in 935 samples of human primary cells, tissues and cell lines. Nature Genetics 49: 1428-1436.

15. Cao Q., and Yip K.Y. (2016) A survey of the computational methods for enhancers and enhancer-target predictions. Computational biology and bioinformatics: Gene regulation 3-27.

(*:co-first authors; #:co-corresponding authors)

Grants

NSFC Young Scientists Fund [PI 1-Jan-22– 31-Dec-24]. “Refining computational predictions of multiscale 3D genome structures in a large number of cancer samples” (HK$ 322,476).
Co-PI of 3 CRF; Co-I of 1 TRS