Research Interest

Oncology

Bioinformatics

Biostatistics

Research Summary

Our lab focuses on developing new biomarkers for several diseases using genomic big data and validating the biomarkers. In the lab, 3 postdoctoral researchers and 1 students used experiments to validate biomarkers that bioinformatics team (2 postdoctoral researchers and 8 students) found. We developed the pipelines of single cell RNA, RNA, and DNA sequecing analysis which are essential methods in bioinformatics. The most studied biomarkers we have developed is diagnostic target for hepatocellular carcinoma. We are developing targeting molecules for hepatocellular carcinoma using carbon quantum dots. In addition, we published many articles for developing and validating biomarkers for several diseases.

Selected publications

1. Identification and Complete Validation of Prognostic Gene Signatures for Human Papillomavirus-Associated Cancers: Integrated Approach Covering Different Anatomical Locations. Kwon EJ, Ha M, Jang JY, Kim YH. Journal of Virology. Epub. 2021. (IF: 4.501, Corresponding author).

2. AML poor prognosis factor, TPD52, is associated with the maintenance of hematopoietic stem cells through regulation of cell proliferation. Kang JW, Kim Y, Lee Y, Myung K, Kim YH. Journal of Cellular Biochemistry. Epub. 2021. (IF: 4.237, Corresponding author)

3. A User-Friendly, Web-Based Integrative Tool (ESurv) for Survival Analysis: Development and Validation Study. Pak K, Oh SO, Goh TS, Heo HJ, Han ME, Jeong DC, Lee CS, Kang J, Choi SJ, Lee S, Kwon EJ, Kang JW, Sun H, Kim YH. Journal of Medical Internet Research. 22(5):e16084. 2020. (IF: 5.034, Corresponding author).

4. Prognostic role of high cathepsin D expression in breast cancer: a systematic review and meta-analysis. Kang J, Yu Y, Jeong S, Lee H, Heo HJ, Park JJ, Na HS, Ko DS, Kim YH. Therapeutic Advances in Medical Oncology. 12:1-13. 2020 (IF: 6.852, Corresponding author)

5. Risk of metastatic pheochromocytoma and paraganlioma in SDHx mutation carriers: A systematic review and updated meta-analysis. Lee H, Jeong S, Yu Y, Kang J, Sun H, Rhee J, Kim YH. Journal of Medical Genetics, 57(4):217-225. 2020 (IF: 4.943, Corresponding author)

6. Prognostic scoring system for osteosarcoma using Network-Regularized high-dimensional Cox regression analysis and potential therapeutic targets. Goh TS, Lee JS, Kim JI, PArk YG, Pak K, Jeong DC, Oh SO, Kim YH. Journal of Cellular Physiology. 234(8): 13851-13857. 2019. (IF: 5.546, Corresponding author)

7. Development of Risk Scoring System for Patients with Papillary Thyroid Cancer. Pak K, Kim YH, Suh S, Goh TS, Jeong DC, Kim SJ, Kim IJ, Han ME, Oh SO. Journal of Cellular and Molecular Medicine. 23(4): 3010-3015. 2019. (IF: 4.486, First author)

8. Prognostic role of TPD52 in acute myeloid leukemia: A retrospective multicohort analysis. Ha M, Han ME, Kim JY, Jeong DC, Oh SO, Kim YH. Journal of Cellular Biochemistry, 120:3672-3678. 2019. (IF: 4.237, Corresponding author)

9. The AP2M1 gene expression is a promising biomarker for predicting survival of patients with hepatocellular carcinoma. Cho SH, Pak K, Jeong DC, Han ME, Oh SO, Kim YH. J Cell Biochem, 120: 4140-4146. 2019. (IF: 4.237, Corresponding author)