Robust sample-specific stability selection with effective error control. Journal of Computational Biology. 2018. To appear
Park H, Konishi S. Sparse common component analysis for multiple high-dimensional datasets via non-centered principal component analysis. Statistical papers. 2018. To appear
Heewon Park, Teppei Shimamura, Seiya Imoto, Satoru Miyano. Adaptive NetworkProfiler for Identifying Cancer Characteristic-Specific Gene Regulatory Networks. Journal of Computational Biology. 2018. 25. 2. 130-145
Heewon Park. Outlier-resistant high-dimensional regression modelling based on distribution-free outlier detection and tuning parameter selection. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION. 2017. 87. 9. 1799-1812
A sparse tensor subspace method for identifying biological modulators based on multilayer gene network analysis
(COMPSTAT2018 2018)
Cancer characteristic-specific analysis via L1-type regularized regression modeling.
(科研費シンポジウム: 生命・自然科学における複雑現象解明のための統計的アプローチ 2018)
Sparse overlapping group lasso for gene selection by incorporating biological knowledge
(International Conference on Mathematics & Computer Science 2017 2017)
Interaction based random elastic net for cancer driver gene selection
(61th World Statistics Congress (ISI2017) 2017)
Robust sparse logistic regression modeling and tuning parameter selection
(2016 CSA & NCCU Joint Statistical Meetings (In Celebration of the 50th Anniversary of Department of Statistics) 2017)
2010 - 2013 Ph.D, Department of Mathematics, Chuo University, Tokyo, Japan.
Work history (4):
2018/09 - 現在 Laboratory of DNA Information Analysis, Human Genome Center, Institute of Medical Science, University of Tokyo Visiting researcher (客員研究員)