Publications



Book or Book Chapters
  1. Chang YJ, Kim H, and Cho H (2016). Data Mining, KNOU Press. (Korean)
  2. Cho H*  and Eo SH (2016). Outlier Detection for Mass Spectrometric Data, Statistical Analysis in Proteomics, edited by Klaus Jung, Springer. (English)
  3. Cho H with 14 more (2011). Bioinformatics, KNOU Press. (Korean)
  4. Cho H*  and Seo W (2010). Statistical Testing and Significance for Large Biological Data Analysis, Statistical Bioinformatics, edited by Jae K Lee, Wiley-Blackwell. (English)
  5. Lee JK, Cho H, and O'Connell M (2009), Frequentist and Bayesian Error Pooling Methods for Enhancing Statistical Power in Small Sample Microarray Data Analysis, Meta-analysis and Combining Information in Genetics and Genomics, edited by Rudy Guerra, David B. Allison, and Darlene Goldstein, Chapman & Hall. (English)

Statistical Methodology Papers in International Journals: SCI(E)/SCOPUS
  1. Bang SW, Eo SH, Jhun M, and Cho H* (2016+). Composite Kernel Quantile Regression, To appear in Communications in Statistics - Simulation and Computation.
  2. Bang SW,  Cho H, and Jhun M (2016). Adaptive Lasso Penalized Censored Composite Quantile Regression, International Journal of Data Mining and Bioinformatics, 15: 22-46.
  3. Bang SW, Eo SH, Cho YM, Jhun M, and Cho H* (2016). Non-crossing Weighted Kernel Quantile Regression with Right Censored Data, Lifetime Data Analysis, 22: 100-121.
  4. Bang SW, Cho H, and Jhun M (2016). Simultaneous Estimation for Non-crossing Multiple Quantile Regression with Right Censored Data, Statistics and Computing 26: 131-147.
  5. Eo SH and Cho H* (2014). Tree-structured Mixed-effects Regression Modeling for Longitudinal Data, Journal of Computational and Graphical Statistics, 23: 720-740.
  6. Choi JPak DEo SH, and Cho H* (2014).  Improving the Risk Classification using Random Regression in High-Throughput High-Dimensional Survival Data, International Journal of Information Processing and Management, 5: 1-9.
  7. Eo SHPak D, Choi J, and Cho H* (2012). Outlier Detection using Projection Quantile Regression for Mass Spectrometry Data with Low Replication, BMC Research Notes, 5(236): 1-9.
  8. Kim Y, Cho H, Kim J, and Jhun M (2010). Median Regression Model for Interval Censored Data, Biometrical Journal, 52:201-208.
  9. Cho H*, Kang JW, and Lee JK (2009). Empirical Bayes Analysis of Unreplicated Microarray Data, Computational Statistics, 24: 393-408.
  10. Cho H*, Yu A, Kim S, Kang JW, and Hong SM (2009). Robust Likelihood-based Survival Modeling with Microarray Data, Journal of Statistical Software, 29:1-16.
  11. Park M and Cho H (2008). Minimum MSE Regression Estimator with Estimated Population, Computational Statistics and Data Analysis, 53:394-404.
  12. Cho H* and Hong SM (2008). Median Regression Tree for Analysis of Censored Survival Data, IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, 38: 715-726.
  13.  Cho H, Kim Y, Jung HJ, Lee SW, and Lee JW (2008). OutlierD: an R Package for Outlier Detection using Quantile Regression on Mass Spectrometry Data, Bioinformatics, 24: 882-884.
  14. Cho H* and Lee JK (2008). Error-Pooling Empirical Bayes Model for Enhanced Statistical Discovery of Differential Expression in Microarray Data, IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, 38: 425-436.
  15. Chopra P, Kang J, Yang J, Cho H, Kim HS and Lee MG (2008). Microarray Data Mining using Landmark Gene-guided Clustering, BMC Bioinformatics, 9:92, 1-13.
  16. Cho H, Smalley DM, Ross MM, Theodorescu D, Ley K and Lee JK (2007). Statistical Identification of Differentially Labelled Peptides from Liquid Chromatography Tandem Mass Spectrometry, Proteomics, 7:3681-3692.
  17. Cho H, Shashkin P,  Dunson D, Jain N, Lee JK, Miller Y, and  Ley K (2007). Induction of Dendritic Cell-like Phenotype in Macrophages during Foam Cell Formation, Physiological Genomics, 29: 149-160.
  18. Cho H* and Lee JK (2006). Response to Comments on Bayesian Hierarchical Error Model for Analysis of Gene Expression Data, Bioinformatics, 22: 2452-2452.
  19. Lee JW, Um SH, Lee JB, Mun JW, and Cho H* (2006). Scoring and Staging Systems using Cox Linear Regression Modeling and Recursive Partitioning,  Methods of Information in Medicine, 45: 37-44 .
  20. Jain N, Cho H, O'Connell M, and Lee JK (2005). Rank-Invariant Resampling-based Estimation of False Discovery Rate for Analysis of Small Sample Microarray Data, BMC Bioinformatics, 6:187, 1-14.
  21. Soukup M, Cho H, and Lee JK (2005). Robust Classification Modeling on Microarray Data Using Misclassification Penalized Posterior, Bioinformatics, 21 (Suppl): i423-i430.
  22. Cho H* and Lee JK (2004). Bayesian Hierarchical Error Model for Analysis of Gene Expression Data, Bioinformatics, 20: 2016-2025.

Scientific Application Papers in International Journals: 
SCI(E)/SCOPUS
  1. Park H, An S, Eo SH, Song KB, Park JH, Kim KP, Lee SS, Cho H, Seo DW, Kim SC, Yu E, and Hong SM. (2014), Survival effect of tumor size and extrapancreatic extension in surgically resected pancreatic cancer patients: proposal for improved T classification, Human Pathology., 45: 2341-2346.
  2. Chung JY, Braunschweig T, Hong SM, Kwon DS, Eo SHCho H, and Hewitt SM (2014), Assessment of vascular endothelial growth factor in formalin fixed, paraffin embedded colon cancer specimens by means of a well-based reverse phase protein array, Proteome Science, 12: 1-8.
  3. Roh J, Knight S, Chung JY, Eo SH, Goggins M, Kim J, Cho H, Yu E, M.D., and Hong SM (2014). S100A4 Expression is a Prognostic Indicator in Small Intestinal Adenocarcinoma, Journal of Clinical Pathology, 67: 216-221.
  4. Kang HJ, Eo SH, Kim SC, Park KM, Lee YJ, Lee SK, Yu E, Cho H*, and Hong SM (2014). Increased Number of Metastatic Lymph Nodes in Adenocarcinoma of the Ampulla of Vater as a Prognostic Factor: A Proposal of New Nodal Classification, Surgery, 155: 74-84.
  5. Huh JY, Yi DY, Eo SHCho H , Park MH, and Kang MS (2013). HLA-A,-B and DRB1 Polymorphism in Korean Defined by Sequence-based Typing of 4128 Cord Blood Units. International Journal of Immunogenetics, 40: 515-523.
  6. Yoon CH,   Youn TJ, Ahn S, Choi DJ, Cho GY, Chae IH, Choi JCho H, Han S, Cho MC, Jeon ES, Chae SC, Kim JJ, Ryu KH, Oh BH (2012). Low Serum Total Cholesterol Level Is a Surrogate Marker, But Not a Risk Factor, for Poor Outcome in Patients Hospitalized With Acute Heart Failure: A Report From the Korean Heart Failure Registry,  Journal of Cardiac Failure, 18: 194-201.
  7. Hong SM, Heaphy CM, Shi C, Eo SHCho H, Meeker AK, Eshleman JR, Hruban RH and Goggins M (2011). Telomeres are shortened in acinar-to-ductal metaplasia lesions associated with pancreatic intraepithelial neoplasia but not in isolated acinar-to-ductal metaplasias, Modern Pathology, 24: 256-266.
  8. Havaleshko DM, Smith SC, Cho H, Cheon S, Owens CR, Lee JK, Liotta LA, Espina V, Wulfkuhle JD, Petricoin EF, and Theodorescu D. (2009). Comparison of Global versus Epidermal Growth Factor Receptor Pathway Profiling for Prediction of Lapatinib Sensitivity in Bladder Cancer. Neoplasia , 11:1185-93.
  9. Hong SM, Pawlick TM, Cho H, Aggarwal B, Goggins M, and Anders RA (2009). Depth of Tumor Invasion Better Predicts Prognosis Than the Current American Joint Committee on Cancer T Classification for Distal Bile Duct Carcinoma. Surgery, 146: 250-257.
  10. Chung JY, Hong SM, Choi BY, Cho H, Yu E, Hewitt SM (2009). The Expression of Phospho-AKT, Phospho-mTOR, and PTEN in Extrahepatic Cholangiocarcinoma, Clinical Cancer Research, 15: 660-667.
  11. Wu Z, Cho H, Hampton GM, and Theodorescu (2009). Cdc6 and Cyclin E2 are PTEM Regulated Genes Associated with Human Prostate Cancer Metastasis, Neoplasia, 11:66-76.
  12. Hong SM, Kim MJ, Jang KT, Yoon GS, Cho H, Frierson H, and Yu E (2008). Adenosquamous Carcinoma, a Rare Subtype of Extrahepatic Bile Duct Carcinoma with Poor Prognosis: Clinicopathologic and Immunohistochemical Studies of 12 Cases with Comparison to 176 Adenocarcinomas, International Journal of Clinical and Experimental Pathology, 1: 147-156.
  13. Aiyar SE, Cho H, Lee J, and Li R (2007). Concerted Transcriptional Regulation by BRCA1 and COBRA1 in Breast Cancer Cells, International Journal of Biological Sciences 3:486-492.
  14. Lee JK, Havaleshko DM, Cho H, Weinstein JN, Kaldjian EP, Karpovich J, Grimshaw A, and Theodorescu D (2007). A Strategy for Predicting the Chemosensitivity of Human Cancers and its Application to Drug Discovery, Proceedings of the National Academy of Sciences of the United States of America (PNAS),  104:13086-13091
  15. Park HY, Fan P, Wang J, Yue W, Aiyar SE, Okouneva T, Cox C, Jordan MA, Demers L, Cho H,  Kim SH,  Song R, and Santen RJ (2007). Effects of   Tetramethoxystilbene (TMS) on Hormone Resistant Breast Cancer Cells: Biological and Biochemical Mechanisms of Action, Cancer Research, 67: 5717-5726
  16. GleissnerCA, Cho H, Dunson D, and Ley K (2007). OxLDL Induces Expression and Activity of Aldose Reductase in Human Monocyte-derived Macrophages, FASEB Journal, 21:969.9
  17. Hong SM, Cho H, Moskaluk CA,Yu E,and Zaika AI (2007). p63 and p73 Expression in Extrahepatic Bile Duct Carcinoma and Their Clinical Significance, Journal of Molecular Histology, 38:167-175.
  18. Havaleshko DT, Cho H, Conaway M, Owens CR, Hampton G, Lee JK, Theodorescu D (2007). Prediction of Drug Combination Chemosensitivity in Human Bladder Cancer, Molecular Cancer Therapeutics, 6:578-86.
  19. Hong SM, Cho H, Moskaluk, C, and Yu E (2007). Measurement of the Invasion Depth of Extrahepatic Bile Duct Carcinoma: An Alternative Method Overcoming the Current T Classification Problems of the AJCC Staging System, American Journal of Surgical Pathology, 31:199-206.
  20. Smalley DM, Root KE, Cho H, Ross MM, and Ley K (2007). Proteomic Discovery of 21 Proteins Expressed in Human Plasma-drived but not Platelete-drived Microparticles, Thrombosis and Haemostasis, 97:67-80.
  21. Garcia BA, Smalley DM, Cho H, Shabanowitz J, Ley K and Hunt DF (2005). The Platelet Microparticle Proteome, Journal of Proteome Research, 4:1516-1521.
  22. Hong SM, Cho H, Frierson HF, Moskaluk CA, Yu E,  and Ro JY (2005). CDX2 and MUC2 Protein Expression in Extrahepatic Bile Duct Carcinoma, American Journal of Clinical Pathology, 124:361-370.
  23. Hong SM, Cho H, Lee OJ, and Ro JY (2005). The Number of Metastatic Lymph Node in Extrahepatic Bile Duct Carcinoma as a Prognostic Factor,  American Journal of Surgical Pathology, 29: 1177-1183.
  24. Hong SM, Kim MJ, Pi DY, Jo D, Yu E, Cho H, and Ro JY (2005). Analysis of Extrahepatic Bile Duct Carcinomas according to New AJCC Staging System Focused on T Classification Problems in 222 Cases,  Cancer, 104: 802-810.
  25. Hong SM, Kim MJ, Cho H, Pi DY, Jo D, Yu E, and Ro JY (2005). Superficial versus Deep Pancreatic Parenchymal Invasion in the Extrahepatic Bile Duct Carcinoma: A Significant Prognostic Factor, Modern Pathology, 18: 969-975.
  26. Lai HC, Cheng Y, Cho H, Kosorok MR, and Farrell PM (2004). Association Between Initial Disease Presentation, Lung Disease Outcomes, and Survival in Patients with Cystic Fibrosis, American Journal of Epidemiology, 159: 537-546.
Statistical Methodology Papers in Domestic Journals
  1. Kim JO, Lee S, and Cho H (2016+). An Analysis Of Scientific Military Training Data Using Joint Model For Longitudinal And Time-to-event Data,  To appear in Journal of the Korean Data Analysis Society.
  2. Kim JO, Cho H, and Bang SW (2016+). Penalized Quantile Regression Tree,  To appear in The Korean Journal of Applied Statistics
  3. Choi JIUm IO, and Cho H* (2016). Outlier Detection in Time Series Data, The Korean Journal of Applied Statistics, 29: 907-920.
  4. Kim JOCho H*, and Kim GG (2015). Analysis of Survivability for Combatants during the Offensive Operation of the Tactical Level, The Korean Journal of Applied Statistics, 28: 921-932.
  5. Bang SW, Jhun MS, and Cho H* (2013). Stepwise Estimation for Multiple Non-crossing Quantile Regression Using Kernel Constraints, The Korean Journal of Applied Statistics, 26: 915-922.
  6. Chun JHMoon HS, Lee SH, and Cho H* (2013). Split Variable Selection in Decision Tree for Mixed Responses, Journal of the Korean Data Analysis Society, 15: 1339-1345.
  7. Woo HSLee SH, and Cho H* (2013). Building Credit Scorig Models with Various Types of Target Variables, Journal of the Korean Data and Information Science Society, 24: 85-94.
  8. Pak D and Cho H* (2012). A Comparison Study of Multivariate Binary and Continuous Outcomes, The Korean Journal of Applied Statistics, 25: 605-612.
  9. Lee SH and Cho H* (2012). Variable Selection in Decision Tree for Count Data,  Journal of the Korean Data Analysis Society, 14: 101-116.
  10. Seo WChoi JJung H, and Cho H* (2010). Reproducibility and Replication of High-dimensional Data, The Korean Journal of Applied Statistics, 23: 1057-1065.
  11. Jeong HC and Cho H (2010). Comparison of the Significant Gene Detection Methods : Focus on EBAM and SAM, Journal of the Korean Data Analysis Society, 12: 3059-3071.
  12. Choi JSLee SH, and Cho H* (2010). A Study for Improving Data Mining Methods for Continuous Response Variables, Journal of the Korean Data and Information Science Society, 21: 917-926.
  13. Jung YHEo SH, Moon HS, and Cho H* (2010). Studying for Improving the Performance of Data Mining Using Ensemble Techniques, Communications of the Korean Statistical Society, 17:561-574.
  14. Jang JYMoon HSLee JH, and Cho H* (2009). Comparison Study of Data Mining Algorithms using Mixed-effects Model, Journal of the Korean Data Analysis Society, 11: 280-303.
  15. Cho H* and Loh WY (2006). Piecewise-constant Tree-structured Modeling for Censored Data, Applied Statistics (Korea University Institute of Statistics), 21:31-53.

Updated on December 2016