Qingnan Liang, Ph.D.

Assistant Professor

755 Research Parkway, Room 353, Oklahoma City, OK 73104

We seek to better understand complex biological systems and human diseases through an integrated approach combining computational modeling, large-scale data analysis, and high-throughput experiments.

Our research develops novel computational methods and software, particularly for single-cell and spatial genomics, and applies creative, knowledge-driven data mining to uncover cellular states, tissue organization, and interactions between cells and their surrounding environments.

We also develop molecular and cell biology experiments to test computationally derived hypotheses. Cancer is one major area of focus, especially how the tumor microenvironment shapes cancer cell plasticity, disease progression, and therapeutic response.

Through this combination of computational and experimental approaches, we aim to uncover general principles of cellular behavior and translate them into a better understanding of human disease.

Education:

Ph.D., Biochemistry, Baylor College of Medicine 2022/3
M.Sc., Biophysics, Fudan University 2016/6
B.Sc., Biological Sciences, Fudan University2013/6

Clinical/Research Interests:

Computational methodology and application in studying human diseases

Novel AI/ML algorithms development and application to single-cell and spatial genomics data.
Interpretable computational modeling of biological processes such as gene regulation, pathway crosstalk,tumor progression, and cell plasticity
Precision medicine approaches through personalized gene network and knowledge graph

Select Publications:

2025

LSGI: interpretable spatial gradient analysis for spatial transcriptomics data.
Liang, Q., Soto, L.S., Haymaker, C., and Chen, K. Genome Biology 26, 238 (2025).
Depletion of effector regulatory T cells associates with major response to induction dual immune checkpoint blockade.
Jiang, X., Rudqvist, N.P., Jiang, B., … et al. Cancer Discovery 15(8), pp.1569–1592 (2025).
CREM is a regulatory checkpoint of CAR and IL-15 signalling in NK cells.
Rafei, H., Basar, R., Acharya, S., … et al. Nature 643(8073), pp.1076–1086 (2025).

2024

Stem cell activity-coupled suppression of endogenous retrovirus governs adult tissue regeneration.
Lyu, Y., Kim, S.J., Humphrey, E.S., … et al. Cell 187(26), pp.7414–7432 (2024).

2023

Pathway centric analysis for single-cell RNA-seq and spatial transcriptomics data with GSDensity.
Liang, Q., Huang, Y., He, S., and Chen, K. Nature Communications 14, 1–17 (2023).
Single-cell multiomics of the human retina reveals hierarchical transcription factor collaboration in mediating cell type-specific effects of genetic variants on gene regulation.
Wang, J., Cheng, X., Liang, Q., … et al. Genome Biology 24(1), p.269 (2023).
A multi-omics atlas of the human retina at single-cell resolution.
Liang, Q., Cheng, X., Wang, J., … et al. Cell Genomics 3, 100298 (2023).
Spatial organization of the mouse retina at single cell resolution by MERFISH.
Choi, J., Li, J., Ferdous, S., Liang, Q., Moffitt, J.R., and Chen, R. Nature Communications 14(1), p.4929 (2023).

2022

Bi-order multimodal integration of single-cell data.
Dou, J., Liang, S., Mohanty, V., … et al. Genome Biology 23(1), p.112 (2022).

2021

Transcript isoforms of Reep6 have distinct functions in the retina.
Liang, Q., Wu, N., Zaneveld, S., … et al. Human Molecular Genetics 30, 1907–1918 (2021).

2019

Single-nuclei RNA-seq on human retinal tissue provides improved transcriptome profiling.
Liang, Q., Dharmat, R., Owen, L., … et al. Nature Communications 10, 1–12 (2019).
A nonhuman primate model of inherited retinal disease.
Moshiri, A., Chen, R., Kim, S., … et al. The Journal of Clinical Investigation 129(2), pp.863–874 (2019).

2015

Structural insights on the catalytic site protection of human carbonyl reductase 1 by glutathione.
Liang, Q., Liu, R., Du, S., and Ding, Y. Journal of Structural Biology 192, 138–144 (2015).

For a complete list of publications, see Google Scholar.

Google Scholar