SUNGKYUNKWAN UNIVERSITY SCHOOL OF MEDICINE
CLOSE HEADER
Laboratory
We are witnessing the beginning of a new generation of medicine. The unprecedented amount of large-scale next generation sequencing data from patients with cancer and other diseases makes data science and artificial intelligence (AI) play a pivotal role in biomedical research. The pressing question is how to best translate the accumulated data into a more effective practice of medicine. Next-Gen Medicine Lab aims to analyze the biological big-data with AI and data science approaches to find a better way to treat cancer. Our research covers highly translationally important questions in multiple fields of cancer biology and medicine with primary focus on precision cancer medicine, tailoring the cancer treatments based on the molecular markup of individual patients from the perspective of AI and data science.
[Selected Publications]
1. Chung Y, Ha JH, Im KC, Lee JS* Accurate Spatial Gene Expression Prediction by integrating Multi-resolution features CVPR (2024) - No. 1 computer vision conference (IF 23.64)
2. AA Sch&228ffer, ..., Lee JS*. A systematic analysis of the landscape of synthetic lethality-driven precision oncology Med 5, 1 (2024). - Medicine journal of CellPress (IF 17.0)
3. Lee JS*, …, Ruppin E*. Synthetic lethality-mediated precision oncology via the tumor transcriptome. Cell 184, 9 (2021). (IF 66.85)
4. R Keshet*, JS Lee*, et al. Targeting purine synthesis in ASS1-expressing tumors enhances the response to immune checkpoint inhibitors. Nature Cancer 1, 894-908 (2020).
5. Lee JS, Ruppin E. Multiomics prediction of response rates to therapies to inhibit programmed cell death 1 and programmed cell death 1 ligand 1. JAMA Oncology 5, 1-5 (2019).
6. Feng X, Arang N, Rigiracciolo DC, Lee JS, et al. A Platform of Synthetic Lethal Gene Interaction Networks Reveals that the GNAQ Uveal Melanoma Oncogene Controls the Hippo Pathway through FAK. Cancer Cell 35, 457-472 (2019).
7. Lee JS*, Adler L*, Karathia H, Carmel N, Rabinovich S, et al. Urea Cycle Dysregulation Generates Clinically Relevant Genomic and Biochemical Signatures. Cell 174, 1559-1570 (2018).
8. Lee JS*, Das A*, Jerby-Arnon, L, Davidson M, Atias D, et al. Harnessing synthetic lethality to predict clinical outcomes of cancer patients Nature Communications 9, 2546 (2018).
1. Chung Y, Ha JH, Im KC, Lee JS* Accurate Spatial Gene Expression Prediction by integrating Multi-resolution features CVPR (2024) - No. 1 computer vision conference (IF 23.64)
2. AA Sch&228ffer, ..., Lee JS*. A systematic analysis of the landscape of synthetic lethality-driven precision oncology Med 5, 1 (2024). - Medicine journal of CellPress (IF 17.0)
3. Lee JS*, …, Ruppin E*. Synthetic lethality-mediated precision oncology via the tumor transcriptome. Cell 184, 9 (2021). (IF 66.85)
4. R Keshet*, JS Lee*, et al. Targeting purine synthesis in ASS1-expressing tumors enhances the response to immune checkpoint inhibitors. Nature Cancer 1, 894-908 (2020).
5. Lee JS, Ruppin E. Multiomics prediction of response rates to therapies to inhibit programmed cell death 1 and programmed cell death 1 ligand 1. JAMA Oncology 5, 1-5 (2019).
6. Feng X, Arang N, Rigiracciolo DC, Lee JS, et al. A Platform of Synthetic Lethal Gene Interaction Networks Reveals that the GNAQ Uveal Melanoma Oncogene Controls the Hippo Pathway through FAK. Cancer Cell 35, 457-472 (2019).
7. Lee JS*, Adler L*, Karathia H, Carmel N, Rabinovich S, et al. Urea Cycle Dysregulation Generates Clinically Relevant Genomic and Biochemical Signatures. Cell 174, 1559-1570 (2018).
8. Lee JS*, Das A*, Jerby-Arnon, L, Davidson M, Atias D, et al. Harnessing synthetic lethality to predict clinical outcomes of cancer patients Nature Communications 9, 2546 (2018).
(Tel) +82-31-299-6107,
(Email) joosang.lee@skku.edu