Welcome to the Computational Technology Innovation & Translation (CTIT) lab at the Lyda Hill Department of Bioinformatics!
Our research is aimed at innovating and translating computational technology to advance biomedical research and medical diagnoses/treatments.

Meet the PI

Dr. Lee has been developing advanced computational algorithms for big, high-dimensional biomedical data for over 20 years. He has worked on numerous biomedical research projects; collaborating successfully with researchers from biomedical engineering, computer science, cell biology, biochemistry, and neuroscience fields, as well as physicians of several different medical specialties. He advanced data analytics for next-generation sequencing (NGS) data, biomedical signals and medical images, and leveraged these as computational tools and models. He was elected as a senior member of IEEE (the world's largest technical professional organization) in 2015 in recognition of his valuable research contributions to science and engineering. He is currently appointed as an Assistant Professor at the Lyda Hill Department of Bioinformatics at UT Southwestern and has a wide spectrum of collaborations across campus with basic science and clinical PIs.

Core Values (3 Ps)

  • Premier computational solutions developed by computational gurus
  • Practical computational solutions applicable in the real world
  • Product-level commercialization-enabled computational solutions

Current UTSW Collaborators


  1. Ramirez, NG.P., Lee, J., Zheng, Y., D’Orso, I. et al. (2022). ADAP1 promotes latent HIV-1 reactivation by selectively tuning KRAS–ERK–AP-1 T cell signaling-transcriptional axis. Nature Communications, 13(1109). https://doi.org/10.1038/s41467-022-28772-0

  2. Ruess, H., Lee, J., Guzman, C., D’Orso, I. et al. (2022). Decoding Human Genome Regulatory Features That Influence HIV-1 Proviral Expression and Fate Through an Integrated Genomics Approach. Bioinformatics and Biology Insights, 16, 11779322211072333.

  3. Jang, S., Lee, J., Mathews, J., Ruess, H., Buszczak, M. et al. (2021). The Drosophila ribosome protein S5 paralog RpS5b promotes germ cell and follicle cell differentiation during oogenesis. Development, 148(19), dev199511.

  4. Hallac, R. R., Lee, J., Kane, A. A. et al. (2021). Assessing outcomes of ear molding therapy by health care providers and convolutional neural network. Scientific reports, 11(1), 1-8.

  5. Zaman, A., Wu, X., Lemoff, A., Lee, J., Bivona, T. G. et al. (2021). Exocyst protein subnetworks integrate Hippo and mTOR signaling to promote virus detection and cancer. Cell reports, 36(5), 109491.

  6. Shembel, A. C., Lee, J., Sacher, J. R., & Johnson, A. M. (2021). Characterization of Primary Muscle Tension Dysphonia Using Acoustic and Aerodynamic Voice Metrics. Journal of Voice. https://doi.org/10.1016/j.jvoice.2021.05.019

  7. Hewitson, L., Mathews, J. A., Lee, J., German, D. C. et al. (2021). Blood biomarker discovery for autism spectrum disorder: A proteomic analysis. PloS one, 16(2), e0246581.

  8. Bhave, M., Mino, R. E., Wang, X., Lee, J., Mettlen, M. et al. (2020). Functional characterization of 67 endocytic accessory proteins using multiparametric quantitative analysis of CCP dynamics. Proceedings of the National Academy of Sciences, 117(50), 31591-31602.

  9. Shah, N., Farhat, A., Wang, Z., Lee, J., McBeth, R., Raman, L. et al. (2020). Neural networks to predict radiographic brain injury in pediatric patients treated with extracorporeal membrane oxygenation. Journal of Clinical Medicine, 9(9), 2718.

See our full publication list on Google Scholar.