1 |
Corvalan AH, Carrasco G, Saavedra K. The genetic and epigenetic bases of gastritis. In: Current Topics in Gastritis (Mozsik G, ed.). Rijeka: InTech, 2013. pp. 79-95.
|
2 |
Marshall BJ, Warren JR. Unidentified curved bacilli in the stomach of patients with gastritis and peptic ulceration. Lancet 1984;1:1311-1315.
|
3 |
Lee HW, Hahm KB, Lee JS, Ju YS, Lee KM, Lee KW. Association of the human leukocyte antigen class II alleles with chronic atrophic gastritis and gastric carcinoma in Koreans. J Dig Dis 2009;10:265-271.
DOI
|
4 |
Zendehdel K, Bahmanyar S, McCarthy S, Nyren O, Andersson B, Ye W. Genetic polymorphisms of glutathione S-transferase genes GSTP1, GSTM1, and GSTT1 and risk of esophageal and gastric cardia cancers. Cancer Causes Control 2009;20:2031-2038.
DOI
|
5 |
Xue H, Liu J, Lin B, Wang Z, Sun J, Huang G. A meta-analysis of interleukin-8 -251 promoter polymorphism associated with gastric cancer risk. PLoS One 2012;7:e28083.
DOI
|
6 |
de Oliveira JG, Silva AE. Polymorphisms of the TLR2 and TLR4 genes are associated with risk of gastric cancer in a Brazilian population. World J Gastroenterol 2012;18:1235-1242.
DOI
ScienceOn
|
7 |
Coussens LM, Werb Z. Inflammation and cancer. Nature 2002;420:860-867.
DOI
ScienceOn
|
8 |
Butte AJ, Kohane IS. Mutual information relevance networks: functional genomic clustering using pairwise entropy measurements. Pac Symp Biocomput 2000:418-429.
|
9 |
Leem S, Jeong HH, Lee J, Wee K, Sohn KA. Fast detection of high-order epistatic interactions in genome-wide association studies using information theoretic measure. Comput Biol Chem 2014;50:19-28.
DOI
|
10 |
Hu T, Sinnott-Armstrong NA, Kiralis JW, Andrew AS, Karagas MR, Moore JH. Characterizing genetic interactions in human disease association studies using statistical epistasis networks. BMC Bioinformatics 2011;12:364.
DOI
|
11 |
Goebel B, Dawy Z, Hagenauer J, Mueller JC. An approximation to the distribution of finite sample size mutual information estimates. In: 2005 IEEE International Conference on Communications, 2005 May 16-20, Seoul. Vol. 2. Seoul: ICC 2005, 2005. pp. 1102-1106.
|
12 |
Hong KW, Kim SS, Kim Y. Genome-wide association study of orthostatic hypotension and supine-standing blood pressure changes in two korean populations. Genomics Inform 2013;11:129-134.
DOI
|
13 |
Lim JE, Oh B. Allelic frequencies of 20 visible phenotype variants in the korean population. Genomics Inform 2013;11:93-96.
DOI
|
14 |
Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007;81:559-575.
DOI
ScienceOn
|
15 |
Liang KC, Wang X. Gene regulatory network reconstruction using conditional mutual information. EURASIP J Bioinform Syst Biol 2008:253894.
|
16 |
Margolin AA, Nemenman I, Basso K, Wiggins C, Stolovitzky G, Dalla Favera R, et al. ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinformatics 2006;7 Suppl 1:S7.
|
17 |
Culverhouse R, Suarez BK, Lin J, Reich T. A perspective on epistasis: limits of models displaying no main effect. Am J Hum Genet 2002;70:461-471.
DOI
ScienceOn
|
18 |
Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 2009;4:44-57.
DOI
|
19 |
Velez DR, White BC, Motsinger AA, Bush WS, Ritchie MD, Williams SM, et al. A balanced accuracy function for epistasis modeling in imbalanced datasets using multifactor dimensionality reduction. Genet Epidemiol 2007;31:306-315.
DOI
ScienceOn
|
20 |
Cline MS, Smoot M, Cerami E, Kuchinsky A, Landys N, Workman C, et al. Integration of biological networks and gene expression data using Cytoscape. Nat Protoc 2007;2:2366-2382.
DOI
ScienceOn
|
21 |
Hochberg Y. A sharper Bonferroni procedure for multiple tests of significance. Biometrika 1988;75:800-802.
DOI
ScienceOn
|
22 |
Pavlopoulos GA, Secrier M, Moschopoulos CN, Soldatos TG, Kossida S, Aerts J, et al. Using graph theory to analyze biological networks. BioData Min 2011;4:10.
DOI
ScienceOn
|
23 |
Sun J, Zhao Z. A comparative study of cancer proteins in the human protein-protein interaction network. BMC Genomics 2010;11 Suppl 3:S5.
|
24 |
Liu Z, Zhang J, Gao Y, Pei L, Zhou J, Gu L, et al. Large-scale characterization of DNA methylation changes in human gastric carcinomas with and without metastasis. Clin Cancer Res 2014;20:4598-4612.
DOI
|
25 |
Kanehisa M, Goto S, Sato Y, Kawashima M, Furumichi M, Tanabe M. Data, information, knowledge and principle: back to metabolism in KEGG. Nucleic Acids Res 2014;42:D199-D205.
DOI
|
26 |
Taniuchi T, Mortensen ER, Ferguson A, Greenson J, Merchant JL. Overexpression of ZBP-89, a zinc finger DNA binding protein, in gastric cancer. Biochem Biophys Res Commun 1997;233:154-160.
DOI
|
27 |
Park KS. How much amount of socioeconomic loss is caused by digestive diseases? Korean J Gastroenterol 2011;58:297-299.
DOI
|
28 |
Yuzhalin A. The role of interleukin DNA polymorphisms in gastric cancer. Hum Immunol 2011;72:1128-1136.
DOI
ScienceOn
|
29 |
Cho YS, Go MJ, Kim YJ, Heo JY, Oh JH, Ban HJ, et al. A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits. Nat Genet 2009;41:527-534.
DOI
ScienceOn
|
30 |
Uchino S, Tsuda H, Noguchi M, Yokota J, Terada M, Saito T, et al. Frequent loss of heterozygosity at the DCC locus in gastric cancer. Cancer Res 1992;52:3099-3102.
|