1 Evans, D. M., "Two-stage two-locus models in genome-wide association" 2 (2): e157-, 2006
2 Hu, J. K., "Testing gene-gene interactions in genome wide association studies" 38 (38): 123-134, 2014
3 황창하, "Support Vector Machine Regression for a Gaussian Fuzzy Model" 한국자료분석학회 6 (6): 431-439, 2004
4 이재용, "Robust Estimation of a Genomic Association against the Imbalance among the Multi-class Phenotypes" 한국자료분석학회 18 (18): 1741-1750, 2016
5 박희창, "Proposition of Modified Balance Cross Entropy in Association Rule Mining" 한국자료분석학회 19 (19): 1733-1741, 2017
6 이희춘, "Prediction Accuracy Increase of Recommender System in Data Scarcity" 한국자료분석학회 12 (12): 1271-1283, 2010
7 Schwarz, D. F., "On safari to random jungle : a fast implementation of random forests for high-dimensional data" 26 (26): 1752-1758, 2010
8 Namkung, J., "New evaluation measures for multifactor dimensionality reduction classifiers in gene-gene interaction analysis" 25 (25): 338-345, 2009
9 Ritchie, M. D., "Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer" 69 : 138-147, 2001
10 Motsinger, A. A., "Multifactor dimensionality reduction: An analysis strategy for modeling and detecting gene-gene interactions in human genetics and pharmacogenomics studies" 2 (2): 318-328, 2006
1 Evans, D. M., "Two-stage two-locus models in genome-wide association" 2 (2): e157-, 2006
2 Hu, J. K., "Testing gene-gene interactions in genome wide association studies" 38 (38): 123-134, 2014
3 황창하, "Support Vector Machine Regression for a Gaussian Fuzzy Model" 한국자료분석학회 6 (6): 431-439, 2004
4 이재용, "Robust Estimation of a Genomic Association against the Imbalance among the Multi-class Phenotypes" 한국자료분석학회 18 (18): 1741-1750, 2016
5 박희창, "Proposition of Modified Balance Cross Entropy in Association Rule Mining" 한국자료분석학회 19 (19): 1733-1741, 2017
6 이희춘, "Prediction Accuracy Increase of Recommender System in Data Scarcity" 한국자료분석학회 12 (12): 1271-1283, 2010
7 Schwarz, D. F., "On safari to random jungle : a fast implementation of random forests for high-dimensional data" 26 (26): 1752-1758, 2010
8 Namkung, J., "New evaluation measures for multifactor dimensionality reduction classifiers in gene-gene interaction analysis" 25 (25): 338-345, 2009
9 Ritchie, M. D., "Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer" 69 : 138-147, 2001
10 Motsinger, A. A., "Multifactor dimensionality reduction: An analysis strategy for modeling and detecting gene-gene interactions in human genetics and pharmacogenomics studies" 2 (2): 318-328, 2006
11 Jing, P. -J., "MACOED: a multi-objective ant colony optimization algorithm for SNP epistasis detection in genome-wide association studies" 31 (31): 634-641, 2015
12 Gyenesei, A., "High-throughput analysis of epistasis in genome-wide association studies with BiForce" 28 (28): 1957-1964, 2012
13 Tuo, S., "FHSA-SED: Two-locus model detection for genome-wide association study with harmony search algorithm" 11 (11): e0150669-, 2016
14 Kam-Thong, T., "EPIBLASTER-fast exhaustive two-locus epistasis detection strategy using graphical processing unit" 19 : 465-471, 2011
15 Li, J., "Detecting gene-gene interactions using a permutation-based random forest method" 9 : 14-, 2016
16 LeCun, Y., "Deep learning" 521 : 436-444, 2015
17 Aflakparast, M., "Cuckoo search epistasis : a new method for exploring significant genetic interactions" 112 : 666-674, 2014
18 Mieth, B., "Combining multiple hypothesis testing with machine learning increases the statistical power of genome-wide association studies" 6 : 36671-, 2016
19 Al-jouie, A., "Chi8 : a GPU program for detecting significant interesting SNPs with the chi-square 8-df test" 8 : 436-, 2015
20 Lee, S., "CARAT-GxG: CUDA-accelerated regression analysis toolkit for large-scale gene-gene interaction with GPU computing system" 13 (13): 27-33, 2014
21 Gola, D., "A roadmap to multifactor dimensionality reduction methods" 17 (17): 293-308, 2016
22 Koo, C. L., "A review for detecting gene-gene interactions using machine learning methods in genetic epidemiology" 432375-, 2013
23 J. Yee, "A modified entropy-based approach for identifying gene-gene interactions in case-control study" 8 (8): e69321-, 2013
24 Li, J., "A fast algorithm for detecting gene-gene interactions in genome-wide association studies" 8 (8): 2292-2318, 2014
25 Uppu, S., "A deep learning approach to detect SNP interactions" 11 (11): 960-975, 2016
26 Velez, D. R., "A balanced accuracy function for epistasis modeling in imbalanced datasets using multifactor dimensionality reduction" 31 : 306-315, 2007