Yongseok Park, PhD

My current research focuses on epigenetic and high throughput genomic data analysis in cancer study. Since January 2012, I have focused on Bioinformatics research such as developing whole genome DNA methylation data analysis pipeline using novel statistical model, RNA sequencing data analysis, microarray and sequencing based gene expression data analysis. In addition, I have developed a web-based statistical tool to predict recurrence of prostate cancer for patients after radiation therapy using Bayesian joint survival-longitudinal modeling. My research interests also include other traditional Biostatistics research including survival analysis, nonparametric analysis and ordered statistics analysis.

2011 | University of Michigan-Ann Arbor | Ph.D.
2007 | University of Michigan-Ann Arbor | Master of Science
Tsinghua University, Beijing P.R.China | Master of Engineering 
Shanghai Jiao Tong University, Shanghai P.R.China | Bachelor of Engineering

BIOST 2083, Linear Models, Fall 2014, Fall 2015,  Fall 2016, Fall 2017, Fall 2018, Fall 2019, Fall 2020

BIOST 2036, Introduction to Health Data Science, Fall 2020

BIOST 2063, Bayesian Data Science, Spring 2021

BIOST 2025, Biostatistics Seminar, Fall 2014  

BIOST 2025, Biostatistics Seminar, Winter 2015  

1. Lin C, Liao SG, Liu P, Lee MT, Park Y, Tseng GC. RNASeqDesign: a framework for ribonucleic acid sequencing genomewide power calculation and study design issues. Journal of the Royal Statistical Society. Series C, Applied statistics. 2018 December; 68:663-704. doi: https://doi.org/10.1111/rssc.12330
2. Liu P, Lin CW, Park Y, Tseng G. MethylSeqDesign: a framework for Methyl-Seq genome-wide power calculation and study design issues. Biostatistics. 2019 May 20;. doi: 10.1093/biostatistics/kxz016
3. Xu Z, Park Y, Zhen B, Zhu B. Designing cancer immunotherapy trials with random treatment time-lag effect. Stat Med. 2018 Dec 30;37(30):4589-4609. doi: 10.1002/sim.7937. Epub 2018 Sep 10
4. Kim, S., Kang, D., Huo, Z., Park, Y., & Tseng, G. C. (2017). Meta-analytic principal component analysis in integrative omics application. Bioinformatics, 34(8), 1321-1328.
5. Seynnaeve, B., Lee, S., Borah, S., Park, Y., Pappo, A., Kirkwood, J. M., Bahrami, A. (2017). Genetic and Epigenetic Alterations of TERT Are Associated with Inferior Outcome in Adolescent and Young Adult Patients with Melanoma. Scientific Reports, 7, 45704
6. Xu Z, Zhen B, Park Y, Zhu B,(2017) Designing therapeutic cancer vaccine trials with delayed treatment effect. Statistics in medicine, 36,592-605
7. Gearhart, T. L., Montelaro, R. C., Schurdak, M. E., Pilcher, C. D., Rinaldo, C. R.,  Kodadek, T., Park, Y., Islam, K., Yurko, R., Marques, E. T. A  Jr. and Burke, D. S.(2016), Selection of a potential diagnostic biomarker for HIV infection from a random library of non-biological synthetic peptoid oligomers. Journal of immunological methods, 435,85-9.
8. Qin, Z., Li, B., Conneely, K. N., Wu, H., Hu, M., Ayyala, D, Park, Y., Jin, V. X., Zhang, F., Zhang, H., Li,  L., Lin, S. (2.16) Statistical challenges in analyzing methylation and long-range chromosomal interaction data. Statistics in biosciences,  8,284-309.
9. Park, Y, Wu, H.(2016) Differential methylation analysis for BS-seq data under general experimental design. Bioinformatics (Oxford, England), 32(10):1446-53.
10. Park, Y., Figueroa, M.E., Rozek, L.S., Sartor, M.A (2014). methylSig: a whole genome DNA methylation analysis pipeline. Bioinformatics, 30, 2414-22.
11. Park, Y., Kalbfleisch, J.D. and Taylor, J.M.G (2014). Confidence intervals under order restriction. Statistica Sinica,  24, 429-445.
12. Taylor, J.M.G., Park, Y., and others (2013), Real-time individual predictions of prostate cancer recurrence using joint  models. Biometrics, 69, 206-213.
13. Park, Y., Taylor, J.M.G. and Kalbfleisch, J.D. (2012), Pointwise nonparametric maximum likelihood estimator of stochastically ordered survivor functions. Biometrika, 99, 327-343. (Supplementary material)
14. Park, Y., Kalbfleisch, J.D. and Taylor, J.M.G. (2012), Constrained nonparametric maximum likelihood estimator of stochastically ordered survivor functions. Canadian Journal of Statistics, 40, 22-39.