Equivalence of two treatments and sample size determination under exponential survival model with censoring. - Jun-mo Nam; Jinheum Kim; Seungyeoun Lee (Comput. Stat. Data Anal., 2005)

Spot Intensity Ratio Statistics in Two-Channel microarray Experiments. - Taesung Park; Kiwoong Kim; Sung-Gon Yi; Jin Hyuk Kim; Yong-Sung Lee; Seungyeoun Lee (J. Bioinform. Comput. Biol., 2007)

Two-way interaction analysis of obesity trait from Korean population using generalized MDR. - Sungyoung Lee 002; Sohee Oh; Min-Seok Kwon; Seungyeoun Lee; Taesung Park (BIBM Workshops, 2010)

Gene-gene interaction analysis for the survival phenotype based on the standardized residuals from parametric regression models. - Seungyeoun Lee; Jinseok Oh; Min-Seok Kwon; Taesung Park (BIBM Workshops, 2011)

A comparative study on gene-set analysis methods for assessing differential expression associated with the survival phenotype. - Seungyeoun Lee; Jinheum Kim; Sunho Lee 001 (BMC Bioinform., 2011)

Gene-gene interaction analysis for the survival phenotype based on the Cox model. - Seungyeoun Lee; Min-Seok Kwon; Jung Mi Oh; Taesung Park (Bioinform., 2012)

Biomarker development for pancreatic ductal adenocarcinoma using integrated analysis of mRNA and miRNA expression. - Min-Seok Kwon; Yongkang Kim; Seungyeoun Lee; Junghyun Namkung; Taegyun Yun; Sung-Gon Yi; Sangjo Han; Meejoo Kang; Sun Whe Kim; Jin-Young Jang; Taesung Park (BIBM, 2014)

Developing cancer prediction model based on stepwise selection by AUC measure for proteomics data. - Yongkang Kim; Seungyeoun Lee; Min-Seok Kwon; Ahrum Na; Yonghwan Choi; Sung-Gon Yi; Junghyun Namkung; Sangjo Han; Meejoo Kang; Sun Whe Kim; Jin-Young Jang; Yikwon Kim; et al. (BIBM, 2015)

Multivariate approach to the analysis of correlated RNA-seq data. - Hyunjin Park; Seungyeoun Lee; Ye Jin Kim; Myung-Sook Choi; Taesung Park (BIBM, 2016)

Gene-set association tests for next-generation sequencing data. - Jaehoon Lee; Young Jin Kim 003; Juyoung Lee; Bong-Jo Kim; Seungyeoun Lee; Taesung Park (Bioinform., 2016)

A unified model based multifactor dimensionality reduction framework for detecting gene-gene interactions. - Wenbao Yu; Seungyeoun Lee; Taesung Park (Bioinform., 2016)

Comparative studies for developing protein based cancer prediction model to maximise the ROC-AUC with various variable selection methods. - Yongkang Kim; Min-Seok Kwon; Yonghwan Choi; Sung-Gon Yi; Junghyun Namkung; Sangjo Han; Wooil Kwon; Sun Whe Kim; Jin-Young Jang; Hyunsoo Kim; Youngsoo Kim; Seungyeoun Lee; et al. (Int. J. Data Min. Bioinform., 2016)

A comparison study of statistical methods for the analysis metagenome data. - Chanyoung Lee; Seungyeoun Lee; Taesung Park (BIBM, 2017)

Statistical methods for metagenomics data analysis. - Chanyoung Lee; Seungyeoun Lee; Taesung Park (Int. J. Data Min. Bioinform., 2017)

Analysis of clustered RNA-seq data. - Hyunjin Park; Seungyeoun Lee; Ye Jin Kim; Myung-Sook Choi; Taesung Park (Int. J. Data Min. Bioinform., 2017)

Unified Cox model based multifactor dimensionality reduction method for gene-gene interaction analysis of the survival phenotype. - Seungyeoun Lee; Donghee Son; Yongkang Kim; Wenbao Yu; Taesung Park (BioData Min., 2018)

Drug response prediction model using a hierarchical structural component modeling method. - Sungtae Kim; Sungkyoung Choi; Jung-Hwan Yoon; Youngsoo Kim; Seungyeoun Lee; Taesung Park (BMC Bioinform., 2018)

A comparative study on the unified model based multifactor dimensionality reduction methods for identifying gene-gene interactions associated with the survival phenotype. - Jung Wun Lee; Seungyeoun Lee (BioData Min., 2021)

Kernel-based hierarchical structural component models for pathway analysis. - Suhyun Hwangbo; Sungyoung Lee 002; Seungyeoun Lee; Heungsun Hwang; Inyoung Kim; Taesung Park (Bioinform., 2022)