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Rastgele Diyabet SNP Olayları ve Moleküler Etkileşim Komşuluğu

Yıl 2019, Cilt: 3 Sayı: 2, 99 - 105, 31.08.2019

Öz

Amaç: Genomik çalışmalar, tip 2 diabetes mellitus (T2DM) dahil olmak üzere, birçok hastalık ve diğer fenotiplerle önemli ilişkileri olanTek Nükleotid Polimorfizmleri koleksiyonu sunmaktadır. T2DM ilişkili SNP olaylarının frekansı genom düzeyinde rastgeleleştirmeanaliziyle incelenebilir. SNP olayları ile eşleştirilen genlere dayanarak, moleküler etkileşim düzeyindeki etkiler incelenebilir.

Gereç ve Yöntemler: İnsan genomu için rastgele SNP olayları oluşturuldu. Farklı T2DM ilişkili SNP olaylarının frekansları incelendi.SNP olaylarıyla eşleştirilmiş genler elde edildi ve bu genlerin doğrudan moleküler etkileşim komşuları incelendi. Ayrıca İnsülinSinyalleşmesi (IS) Yolağının, T2DM ilişkili SNP olaylarının hedefinde olup olmadığı kontrol edildi.

Bulgular: En az bir adet T2DM ilişkili SNP’nin rastgele olarak gözlemlenmesi olası olarak bulundu. Ağ komşuluğu göz önüne alındığında,rastgele SNP olaylarının etkisi genişledi. Bazı SNP’ler ve bunlarla eşleştirilmiş olan genler, diğerlerine göre daha sıkça hedeflendi. ISYolağı üyeleri nadiren hedeflendi, ancak ağ komşuluğu bu yolağa olan etkiyi de genişletti.

Sonuç: Bireysel genomlarda rastgele beklenen varyasyonlar diyabet duyarlılığını muhtemelen etkiler. Ağ düzeyi etkileşimler genomikvaryasyonların etkisini genişletir.

Kaynakça

  • 1. 1000 Genomes Project Consortium, Auton A, Brooks LD, Durbin RM, Garrison EP,Kang HM, Korbel JO, Marchini JL, McCarthy S, McVean GA, Abecasis GR. A globalreference for human genetic variation. Nature. 2015;526(7571):68-74. doi:10.1038/nature15393.
  • 2. Hardy J, Singleton A. Genomewide association studies and human disease. N EnglJ Med. 2009;360(17):1759-68. doi: 10.1056/NEJMra0808700.
  • 3. Visscher PM, Wray NR, Zhang Q, Sklar P, McCarthy MI, Brown MA, Yang J. 10Years of GWAS Discovery: Biology, Function, and Translation. Am J Hum Genet.2017;101(1):5-22. doi: 10.1016/j.ajhg.2017.06.005.
  • 4. Kharroubi AT, Darwish HM. Diabetes mellitus: The epidemic of the century.World J Diabetes. 2015;6(6):850-67. doi: 10.4239/wjd.v6.i6.850.
  • 5. Ginter E, Simko V. Type 2 diabetes mellitus, pandemic in 21st century. Adv ExpMed Biol. 2012;771:42-50.
  • 6. Buniello A, MacArthur JAL, Cerezo M, Harris LW, Hayhurst J, Malangone C,McMahon A, Morales J, Mountjoy E, Sollis E, Suveges D, Vrousgou O, Whetzel PL,Amode R, Guillen JA, Riat HS, Trevanion SJ, Hall P, Junkins H, Flicek P, Burdett T, Hindorff LA, Cunningham F, Parkinson H. The NHGRI-EBI GWAS Catalog ofpublished genome-wide association studies, targeted arrays and summary statistics2019. Nucleic Acids Res. 2019;47(D1):D1005-D1012. doi: 10.1093/nar/gky1120.
  • 7. Xue A, Wu Y, Zhu Z, Zhang F, Kemper KE, Zheng Z, Yengo L, Lloyd-Jones LR,Sidorenko J, Wu Y; eQTLGen Consortium, McRae AF, Visscher PM, Zeng J, Yang J.Genome-wide association analyses identify 143 risk variants and putativeregulatory mechanisms for type 2 diabetes. Nat Commun. 2018; 9(1):2941.doi: 10.1038/s41467-018-04951-w.
  • 8. Auffray C, Chen Z, Hood L. Systems medicine: the future of medical genomicsand healthcare. Genome Med. 2009;1(1):2. doi: 10.1186/gm2.
  • 9. Caldera M, Buphamalai P, Müller F, Menche J. Interactome-based approaches to human disease. Curr Opin Syst Biol. 2017; 3:88-94. doi: 10.1016/j.coisb.2017.04.015.
  • 10. Fröjdö S, Vidal H, Pirola L. Alterations of insulin signaling in type 2diabetes: a review of the current evidence from humans. Biochim Biophys Acta.2009;1792(2):83-92. doi: 10.1016/j.bbadis.2008.10.019.
  • 11. Stark C, Breitkreutz BJ, Reguly T, Boucher L, Breitkreutz A, Tyers M. BioGRID:a general repository for interaction datasets. Nucleic Acids Res. 2006;34(Database issue):D535-9.
  • 12. Yates B, Braschi B, Gray KA, Seal RL, Tweedie S, Bruford EA. Genenames.org:the HGNC and VGNC resources in 2017. Nucleic Acids Res. 2017;45(D1):D619-D625. doi: 10.1093/nar/gkw1033.
  • 13. Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. NucleicAcids Res. 2000;28(1):27-30.
  • 14. Kanehisa M, Furumichi M, Tanabe M, Sato Y, Morishima K. KEGG: new perspectiveson genomes, pathways, diseases and drugs. Nucleic Acids Res. 2017;45(D1):D353-D361. doi: 10.1093/nar/gkw1092.
  • 15. Kanehisa M, Sato Y, Furumichi M, Morishima K, Tanabe M. New approach forunderstanding genome variations in KEGG. Nucleic Acids Res. 2019;47(D1):D590-D595. doi: 10.1093/nar/gky962.
  • 16. Hubberten M, Bochenek G, Chen H, Häsler R, Wiehe R, Rosenstiel P, Jepsen S,Dommisch H, Schaefer AS. Linear isoforms of the long noncoding RNA CDKN2B-AS1regulate the c-myc-enhancer binding factor RBMS1. Eur J Hum Genet. 2019;27(1):80-89. doi: 10.1038/s41431-018-0210-7.
  • 17. Aken BL, Ayling S, Barrell D, Clarke L, Curwen V, Fairley S, Fernandez BanetJ, Billis K, García Girón C, Hourlier T, Howe K, Kähäri A, Kokocinski F, MartinFJ, Murphy DN, Nag R, Ruffier M, Schuster M, Tang YA, Vogel JH, White S, Zadissa A, Flicek P, Searle SM. The Ensembl gene annotation system. Database (Oxford).2016;2016. pii: baw093. doi: 10.1093/database/baw093.
  • 18. Brambillasca S, Altkrueger A, Colombo SF, Friederich A, Eickelmann P, Mark M, Borgese N, Solimena M. CDK5 regulatory subunit-associated protein 1-like 1(CDKAL1) is a tail-anchored protein in the endoplasmic reticulum (ER) ofinsulinoma cells. J Biol Chem. 2012;287(50):41808-19. doi:10.1074/jbc.M112.376558.
  • 19. Groenewoud MJ, Dekker JM, Fritsche A, Reiling E, Nijpels G, Heine RJ, Maassen JA, Machicao F, Schäfer SA, Häring HU, 't Hart LM, van Haeften TW. Variants ofCDKAL1 and IGF2BP2 affect first-phase insulin secretion during hyperglycaemicclamps. Diabetologia. 2008;51(9):1659-63. doi: 10.1007/s00125-008-1083-z.
  • 20. Chen BH, Hivert MF, Peters MJ, Pilling LC, Hogan JD, Pham LM, Harries LW, Fox CS, Bandinelli S, Dehghan A, Hernandez DG, Hofman A, Hong J, Joehanes R, Johnson AD, Munson PJ, Rybin DV, Singleton AB, Uitterlinden AG, Ying S; MAGICInvestigators, Melzer D, Levy D, van Meurs JB, Ferrucci L, Florez JC, Dupuis J,Meigs JB, Kolaczyk ED. Peripheral Blood Transcriptomic Signatures of FastingGlucose and Insulin Concentrations. Diabetes. 2016;65(12):3794-3804.
  • 21. Boini KM, Graf D, Hennige AM, Koka S, Kempe DS, Wang K, Ackermann TF, FöllerM, Vallon V, Pfeifer K, Schleicher E, Ullrich S, Häring HU, Häussinger D, Lang F.Enhanced insulin sensitivity of gene-targeted mice lacking functional KCNQ1. Am JPhysiol Regul Integr Comp Physiol. 2009;296(6):R1695-701. doi:10.1152/ajpregu.90839.2008.
  • 22. Yamagata K, Senokuchi T, Lu M, Takemoto M, Fazlul Karim M, Go C, Sato Y, HattaM, Yoshizawa T, Araki E, Miyazaki J, Song WJ. Voltage-gated K+ channel KCNQ1regulates insulin secretion in MIN6 β-cell line. Biochem Biophys Res Commun. 2011;407(3):620-5. doi: 10.1016/j.bbrc.2011.03.083.
  • 23. Nilsson M, Dahlman I, Jiao H, Gustafsson JA, Arner P, Dahlman-Wright K. Impactof estrogen receptor gene polymorphisms and mRNA levels on obesity andlipolysis--a cohort study. BMC Med Genet. 2007; 8:73.
  • 24. Herrera-Lopez EE, Castelan-Martinez OD, Suarez-Sanchez F, Gomez-Zamudio JH,Peralta-Romero JJ, Cruz M, Valladares-Salgado A. The rs1256031 of estrogenreceptor β gene is associated with type 2 diabetes. Diabetes Metab Syndr. 2018; 12(5):631-633. doi: 10.1016/j.dsx.2018.04.018.
  • 25. Lee JM, Choi SS, Lee YH, Khim KW, Yoon S, Kim BG, Nam D, Suh PG, Myung K, ChoiJH. The E3 ubiquitin ligase TRIM25 regulates adipocyte differentiation viaproteasome-mediated degradation of PPARγ. Exp Mol Med. 2018; 50(10):135.doi: 10.1038/s12276-018-0162-6.
  • 26. Li X, Zeng L, Cao C, Lu C, Lian W, Han J, Zhang X, Zhang J, Tang T, Li M. Longnoncoding RNA MALAT1 regulates renal tubular epithelial pyroptosis by modulatedmiR-23c targeting of ELAVL1 in diabetic nephropathy. Exp Cell Res. 2017; 350(2):327-335. doi: 10.1016/j.yexcr.2016.12.006.
  • 27. Ruan X, Li P, Cangelosi A, Yang L, Cao H. A Long Non-coding RNA, lncLGR,Regulates Hepatic Glucokinase Expression and Glycogen Storage during Fasting.Cell Rep. 2016;14(8):1867-75. doi: 10.1016/j.celrep.2016.01.062.
  • 28. Gao C, Huang W, Kanasaki K, Xu Y. The role of ubiquitination and sumoylationin diabetic nephropathy. Biomed Res Int. 2014;2014:160692. doi:10.1155/2014/160692.
  • 29. Zhao J, Xiong X, Li Y, Liu X, Wang T, Zhang H, Jiao Y, Jiang J, Zhang H, Tang Q, Gao X, Li X, Lu Y, Liu B, Hu C, Li X. Hepatic F-Box Protein FBXW7 MaintainsGlucose Homeostasis Through Degradation of Fetuin-A. Diabetes. 2018; 67(5):818-830. doi: 10.2337/db17-1348.
  • 30. Isshiki K, He Z, Maeno Y, Ma RC, Yasuda Y, Kuroki T, White GS, Patti ME, Weir GC, King GL. Insulin regulates SOCS2 expression and the mitogenic effect of IGF-1in mesangial cells. Kidney Int. 2008;74(11):1434-43. doi:10.1038/ki.2008.403.

Random SNP Events for Diabetes and Their Molecular Interaction Neighborhood

Yıl 2019, Cilt: 3 Sayı: 2, 99 - 105, 31.08.2019

Öz

Aim: Genomics studies provide a collection of Single Nucleotide Polymorphisms (SNPs) which are significantly associated with various diseases and other conditions, including type 2 diabetes mellitus (T2DM). Frequency of T2DM associated SNP events could be investigated by genome scale randomizations. Based on mapped genes for SNP events, molecular interaction neighborhood could also be analyzed.

Material and Methods: Random SNP events were generated for the human genome. Frequencies of different unique T2DM associated SNP events were analyzed. Mapped genes for the SNPs were collected and their direct molecular interaction neighborhood was analyzed. Insulin Signaling (IS) Pathway was also checked to observe if it was targeted by the T2DM associated SNPs.

Results: Having at least a single T2DM associated SNP randomly, was observed to be likely. The effect of random SNP events expanded, when network neighborhood was considered. Some SNPs and their mapped genes were more frequently targeted than others. Although IS Pathway members were rarely targeted, network neighborhood also expanded the influence on IS Pathway.

Conclusion: Randomly expected variations in individual genomes are likely to affect diabetes susceptibility. Consideration of network level relationships enlarge the effect of the genomic variations.

Kaynakça

  • 1. 1000 Genomes Project Consortium, Auton A, Brooks LD, Durbin RM, Garrison EP,Kang HM, Korbel JO, Marchini JL, McCarthy S, McVean GA, Abecasis GR. A globalreference for human genetic variation. Nature. 2015;526(7571):68-74. doi:10.1038/nature15393.
  • 2. Hardy J, Singleton A. Genomewide association studies and human disease. N EnglJ Med. 2009;360(17):1759-68. doi: 10.1056/NEJMra0808700.
  • 3. Visscher PM, Wray NR, Zhang Q, Sklar P, McCarthy MI, Brown MA, Yang J. 10Years of GWAS Discovery: Biology, Function, and Translation. Am J Hum Genet.2017;101(1):5-22. doi: 10.1016/j.ajhg.2017.06.005.
  • 4. Kharroubi AT, Darwish HM. Diabetes mellitus: The epidemic of the century.World J Diabetes. 2015;6(6):850-67. doi: 10.4239/wjd.v6.i6.850.
  • 5. Ginter E, Simko V. Type 2 diabetes mellitus, pandemic in 21st century. Adv ExpMed Biol. 2012;771:42-50.
  • 6. Buniello A, MacArthur JAL, Cerezo M, Harris LW, Hayhurst J, Malangone C,McMahon A, Morales J, Mountjoy E, Sollis E, Suveges D, Vrousgou O, Whetzel PL,Amode R, Guillen JA, Riat HS, Trevanion SJ, Hall P, Junkins H, Flicek P, Burdett T, Hindorff LA, Cunningham F, Parkinson H. The NHGRI-EBI GWAS Catalog ofpublished genome-wide association studies, targeted arrays and summary statistics2019. Nucleic Acids Res. 2019;47(D1):D1005-D1012. doi: 10.1093/nar/gky1120.
  • 7. Xue A, Wu Y, Zhu Z, Zhang F, Kemper KE, Zheng Z, Yengo L, Lloyd-Jones LR,Sidorenko J, Wu Y; eQTLGen Consortium, McRae AF, Visscher PM, Zeng J, Yang J.Genome-wide association analyses identify 143 risk variants and putativeregulatory mechanisms for type 2 diabetes. Nat Commun. 2018; 9(1):2941.doi: 10.1038/s41467-018-04951-w.
  • 8. Auffray C, Chen Z, Hood L. Systems medicine: the future of medical genomicsand healthcare. Genome Med. 2009;1(1):2. doi: 10.1186/gm2.
  • 9. Caldera M, Buphamalai P, Müller F, Menche J. Interactome-based approaches to human disease. Curr Opin Syst Biol. 2017; 3:88-94. doi: 10.1016/j.coisb.2017.04.015.
  • 10. Fröjdö S, Vidal H, Pirola L. Alterations of insulin signaling in type 2diabetes: a review of the current evidence from humans. Biochim Biophys Acta.2009;1792(2):83-92. doi: 10.1016/j.bbadis.2008.10.019.
  • 11. Stark C, Breitkreutz BJ, Reguly T, Boucher L, Breitkreutz A, Tyers M. BioGRID:a general repository for interaction datasets. Nucleic Acids Res. 2006;34(Database issue):D535-9.
  • 12. Yates B, Braschi B, Gray KA, Seal RL, Tweedie S, Bruford EA. Genenames.org:the HGNC and VGNC resources in 2017. Nucleic Acids Res. 2017;45(D1):D619-D625. doi: 10.1093/nar/gkw1033.
  • 13. Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. NucleicAcids Res. 2000;28(1):27-30.
  • 14. Kanehisa M, Furumichi M, Tanabe M, Sato Y, Morishima K. KEGG: new perspectiveson genomes, pathways, diseases and drugs. Nucleic Acids Res. 2017;45(D1):D353-D361. doi: 10.1093/nar/gkw1092.
  • 15. Kanehisa M, Sato Y, Furumichi M, Morishima K, Tanabe M. New approach forunderstanding genome variations in KEGG. Nucleic Acids Res. 2019;47(D1):D590-D595. doi: 10.1093/nar/gky962.
  • 16. Hubberten M, Bochenek G, Chen H, Häsler R, Wiehe R, Rosenstiel P, Jepsen S,Dommisch H, Schaefer AS. Linear isoforms of the long noncoding RNA CDKN2B-AS1regulate the c-myc-enhancer binding factor RBMS1. Eur J Hum Genet. 2019;27(1):80-89. doi: 10.1038/s41431-018-0210-7.
  • 17. Aken BL, Ayling S, Barrell D, Clarke L, Curwen V, Fairley S, Fernandez BanetJ, Billis K, García Girón C, Hourlier T, Howe K, Kähäri A, Kokocinski F, MartinFJ, Murphy DN, Nag R, Ruffier M, Schuster M, Tang YA, Vogel JH, White S, Zadissa A, Flicek P, Searle SM. The Ensembl gene annotation system. Database (Oxford).2016;2016. pii: baw093. doi: 10.1093/database/baw093.
  • 18. Brambillasca S, Altkrueger A, Colombo SF, Friederich A, Eickelmann P, Mark M, Borgese N, Solimena M. CDK5 regulatory subunit-associated protein 1-like 1(CDKAL1) is a tail-anchored protein in the endoplasmic reticulum (ER) ofinsulinoma cells. J Biol Chem. 2012;287(50):41808-19. doi:10.1074/jbc.M112.376558.
  • 19. Groenewoud MJ, Dekker JM, Fritsche A, Reiling E, Nijpels G, Heine RJ, Maassen JA, Machicao F, Schäfer SA, Häring HU, 't Hart LM, van Haeften TW. Variants ofCDKAL1 and IGF2BP2 affect first-phase insulin secretion during hyperglycaemicclamps. Diabetologia. 2008;51(9):1659-63. doi: 10.1007/s00125-008-1083-z.
  • 20. Chen BH, Hivert MF, Peters MJ, Pilling LC, Hogan JD, Pham LM, Harries LW, Fox CS, Bandinelli S, Dehghan A, Hernandez DG, Hofman A, Hong J, Joehanes R, Johnson AD, Munson PJ, Rybin DV, Singleton AB, Uitterlinden AG, Ying S; MAGICInvestigators, Melzer D, Levy D, van Meurs JB, Ferrucci L, Florez JC, Dupuis J,Meigs JB, Kolaczyk ED. Peripheral Blood Transcriptomic Signatures of FastingGlucose and Insulin Concentrations. Diabetes. 2016;65(12):3794-3804.
  • 21. Boini KM, Graf D, Hennige AM, Koka S, Kempe DS, Wang K, Ackermann TF, FöllerM, Vallon V, Pfeifer K, Schleicher E, Ullrich S, Häring HU, Häussinger D, Lang F.Enhanced insulin sensitivity of gene-targeted mice lacking functional KCNQ1. Am JPhysiol Regul Integr Comp Physiol. 2009;296(6):R1695-701. doi:10.1152/ajpregu.90839.2008.
  • 22. Yamagata K, Senokuchi T, Lu M, Takemoto M, Fazlul Karim M, Go C, Sato Y, HattaM, Yoshizawa T, Araki E, Miyazaki J, Song WJ. Voltage-gated K+ channel KCNQ1regulates insulin secretion in MIN6 β-cell line. Biochem Biophys Res Commun. 2011;407(3):620-5. doi: 10.1016/j.bbrc.2011.03.083.
  • 23. Nilsson M, Dahlman I, Jiao H, Gustafsson JA, Arner P, Dahlman-Wright K. Impactof estrogen receptor gene polymorphisms and mRNA levels on obesity andlipolysis--a cohort study. BMC Med Genet. 2007; 8:73.
  • 24. Herrera-Lopez EE, Castelan-Martinez OD, Suarez-Sanchez F, Gomez-Zamudio JH,Peralta-Romero JJ, Cruz M, Valladares-Salgado A. The rs1256031 of estrogenreceptor β gene is associated with type 2 diabetes. Diabetes Metab Syndr. 2018; 12(5):631-633. doi: 10.1016/j.dsx.2018.04.018.
  • 25. Lee JM, Choi SS, Lee YH, Khim KW, Yoon S, Kim BG, Nam D, Suh PG, Myung K, ChoiJH. The E3 ubiquitin ligase TRIM25 regulates adipocyte differentiation viaproteasome-mediated degradation of PPARγ. Exp Mol Med. 2018; 50(10):135.doi: 10.1038/s12276-018-0162-6.
  • 26. Li X, Zeng L, Cao C, Lu C, Lian W, Han J, Zhang X, Zhang J, Tang T, Li M. Longnoncoding RNA MALAT1 regulates renal tubular epithelial pyroptosis by modulatedmiR-23c targeting of ELAVL1 in diabetic nephropathy. Exp Cell Res. 2017; 350(2):327-335. doi: 10.1016/j.yexcr.2016.12.006.
  • 27. Ruan X, Li P, Cangelosi A, Yang L, Cao H. A Long Non-coding RNA, lncLGR,Regulates Hepatic Glucokinase Expression and Glycogen Storage during Fasting.Cell Rep. 2016;14(8):1867-75. doi: 10.1016/j.celrep.2016.01.062.
  • 28. Gao C, Huang W, Kanasaki K, Xu Y. The role of ubiquitination and sumoylationin diabetic nephropathy. Biomed Res Int. 2014;2014:160692. doi:10.1155/2014/160692.
  • 29. Zhao J, Xiong X, Li Y, Liu X, Wang T, Zhang H, Jiao Y, Jiang J, Zhang H, Tang Q, Gao X, Li X, Lu Y, Liu B, Hu C, Li X. Hepatic F-Box Protein FBXW7 MaintainsGlucose Homeostasis Through Degradation of Fetuin-A. Diabetes. 2018; 67(5):818-830. doi: 10.2337/db17-1348.
  • 30. Isshiki K, He Z, Maeno Y, Ma RC, Yasuda Y, Kuroki T, White GS, Patti ME, Weir GC, King GL. Insulin regulates SOCS2 expression and the mitogenic effect of IGF-1in mesangial cells. Kidney Int. 2008;74(11):1434-43. doi:10.1038/ki.2008.403.
Toplam 30 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Sağlık Kurumları Yönetimi
Bölüm Makaleler
Yazarlar

Ertuğrul Dalgıç 0000-0003-0536-4447

Yayımlanma Tarihi 31 Ağustos 2019
Kabul Tarihi 22 Ağustos 2019
Yayımlandığı Sayı Yıl 2019 Cilt: 3 Sayı: 2

Kaynak Göster

APA Dalgıç, E. (2019). Random SNP Events for Diabetes and Their Molecular Interaction Neighborhood. Türkiye Diyabet Ve Obezite Dergisi, 3(2), 99-105.
AMA Dalgıç E. Random SNP Events for Diabetes and Their Molecular Interaction Neighborhood. Turk J Diab Obes. Ağustos 2019;3(2):99-105.
Chicago Dalgıç, Ertuğrul. “Random SNP Events for Diabetes and Their Molecular Interaction Neighborhood”. Türkiye Diyabet Ve Obezite Dergisi 3, sy. 2 (Ağustos 2019): 99-105.
EndNote Dalgıç E (01 Ağustos 2019) Random SNP Events for Diabetes and Their Molecular Interaction Neighborhood. Türkiye Diyabet ve Obezite Dergisi 3 2 99–105.
IEEE E. Dalgıç, “Random SNP Events for Diabetes and Their Molecular Interaction Neighborhood”, Turk J Diab Obes, c. 3, sy. 2, ss. 99–105, 2019.
ISNAD Dalgıç, Ertuğrul. “Random SNP Events for Diabetes and Their Molecular Interaction Neighborhood”. Türkiye Diyabet ve Obezite Dergisi 3/2 (Ağustos 2019), 99-105.
JAMA Dalgıç E. Random SNP Events for Diabetes and Their Molecular Interaction Neighborhood. Turk J Diab Obes. 2019;3:99–105.
MLA Dalgıç, Ertuğrul. “Random SNP Events for Diabetes and Their Molecular Interaction Neighborhood”. Türkiye Diyabet Ve Obezite Dergisi, c. 3, sy. 2, 2019, ss. 99-105.
Vancouver Dalgıç E. Random SNP Events for Diabetes and Their Molecular Interaction Neighborhood. Turk J Diab Obes. 2019;3(2):99-105.

Zonguldak Bülent Ecevit Üniversitesi Obezite ve Diyabet Uygulama ve Araştırma Merkezi’nin bilimsel yayım organıdır.

Web: https://obdm.beun.edu.tr/  Twitter: https://twitter.com/obezite_diyabet     Instagram: https://www.instagram.com/zbeuobezitediyabet/