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Journal articles on the topic 'Gene Relation'

Author: Grafiati

Published: 4 June 2021

Last updated: 8 February 2022

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1

Barkha Singh, Barkha Singh, Rashmi Rashmi, Sunil Kumar Rai, Sangeeta Rai, and Royana Singh Royana Singh. "In-Silico Study of Neural Tube Defect in Relation to FOHL1 Gene." International Journal of Scientific Research 3, no. 4 (June 1, 2012): 366–67. http://dx.doi.org/10.15373/22778179/apr2014/130.

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2

KULIG, Hanna, Tomasz KAŁŁAS, Inga KOWALEWSKA-ŁUCZAK, Melania KUNICKA, and Katarzyna WOJDAK-MAKSYMIEC. "SLC27A1 GENE POLYMORPHISM ANALYSIS IN RELATION TO MILK PRODUCTION TRAITS IN JERSEY COWS." Folia Pomeranae Universitatis Technologiae Stetinensis Agricultura, Alimentaria, Piscaria et Zootechnica 326, no. 38 (September 5, 2016): 81–88. http://dx.doi.org/10.21005/aapz2016.38.2.07.

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3

Kim, Dokyoon, Hyunjung Shin, Je-Gun Joung, Su-Yeon Lee, and Ju Han Kim. "Intra-relation reconstruction from inter-relation: miRNA to gene expression." BMC Systems Biology 7, Suppl 3 (2013): S8. http://dx.doi.org/10.1186/1752-0509-7-s3-s8.

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4

Cain, J. "Ethics in relation to gene therapy." International Journal of Gynecology & Obstetrics 70 (2000): B17. http://dx.doi.org/10.1016/s0020-7292(00)86131-7.

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5

Song, Min, Nam-Gi Han, Yong-Hwan Kim, Ying Ding, and Tamy Chambers. "Discovering Implicit Entity Relation with the Gene-Citation-Gene Network." PLoS ONE 8, no. 12 (December 17, 2013): e84639. http://dx.doi.org/10.1371/journal.pone.0084639.

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6

McDonald, D. M., H. Chen, H. Su, and B. B. Marshall. "Extracting gene pathway relations using a hybrid grammar: the Arizona Relation Parser." Bioinformatics 20, no. 18 (July 15, 2004): 3370–78. http://dx.doi.org/10.1093/bioinformatics/bth409.

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7

Geiß, Manuela, John Anders, Peter F. Stadler, Nicolas Wieseke, and Marc Hellmuth. "Reconstructing gene trees from Fitch’s xenology relation." Journal of Mathematical Biology 77, no. 5 (June 27, 2018): 1459–91. http://dx.doi.org/10.1007/s00285-018-1260-8.

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8

Sartor, Maureen A., Vasudeva Mahavisno, Venkateshwar G. Keshamouni, James Cavalcoli, Zachary Wright, Alla Karnovsky, Rork Kuick, et al. "ConceptGen: a gene set enrichment and gene set relation mapping tool." Bioinformatics 26, no. 4 (December 9, 2009): 456–63. http://dx.doi.org/10.1093/bioinformatics/btp683.

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9

Hall, Judith G., and Judith E. Allanson. "Neurofibromatosis I: Predicting the relation of gene structure to gene function." American Journal of Medical Genetics 38, no. 1 (January 1, 1991): 135. http://dx.doi.org/10.1002/ajmg.1320380128.

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10

Kuniholm, M. H., K. Anastos, A. Kovacs, X. Gao, D. Marti, A. Sette, R. M. Greenblatt, et al. "Relation of HLA class I and II supertypes with spontaneous clearance of hepatitis C virus." Genes & Immunity 14, no. 5 (May 2, 2013): 330–35. http://dx.doi.org/10.1038/gene.2013.25.

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11

Abdelsalam, Tawfik, Tarek Karkour, Magdy Elbordiny, Dina Shalaby, and Ziad S. Abouzeid. "Thrombophilia gene mutations in relation to recurrent miscarriage." International Journal of Reproduction, Contraception, Obstetrics and Gynecology 7, no. 3 (February 27, 2018): 796. http://dx.doi.org/10.18203/2320-1770.ijrcog20180857.

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Background: Recurrent pregnancy loss is multifactorial involving clinical and biological risk factors. Evidence addressed the association of inherited thrombophilia with recurrent pregnancy loss and other serious pregnancy complications. However, the relation between thrombophilia associated gene mutations and adverse obstetric outcome is controversial and data in the literature are inconsistent. The aim of this study was to investigate the prevalence of thrombophilia associated gene mutations (factor V Leiden, prothrombin gene G20210A and methylene-tetrahydrofolate reductase MTHFR C677T) in relation to recurrent miscarriage.Methods: Case control study conducted on 200 women recruited from Elshatby Maternity Hospital clinics. The cases group included 100 women with history of three or more unexplained consecutive pregnancy losses, while 100 healthy age matched women with no history of recurrent miscarriages served as controls. Blood samples were collected from all women enrolled in the study for DNA extraction and genotype analysis. Factor V, prothrombin and MTHFR gene mutations were assayed based on polymerase chain reaction (PCR) and reverse-hybridization.Results: The prevalence of Factor V Leiden and prothrombin gene G20210A mutations did not differ significantly between cases and controls. However, MTHFR C667T mutations and the total prevalence of the three gene mutations were significantly increased in the patients group compared to controls (p=0.001, p=0.003 respectively). The prevalence of combined thrombophilia of Factor V Leiden and MTHFR C677T was significantly increased in the patients group compared to controls (p=0.032). Regarding homozygosity of each of the gene mutations, no homozygosity was detected in controls and heterozygotes were significantly increased in the patients group compared to homozygotes.Conclusions: MTHFR mutations and the total prevalence of the three gene mutations were significantly increased in the patients group compared to controls. There was a significant increase in the prevalence of combined thrombophilia (Factor V Leiden and MTHFR C677T) in the patients group compared to controls without involvement of prothrombin gene.

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12

Al-Nuaimi, Bashar, Christophe Guyeux, Bassam AlKindy, Michel Salomon, and Jean-Francois Couchot. "Relation between Gene Content and Taxonomy in Chloroplasts." International Journal of Bioscience, Biochemistry and Bioinformatics 7, no. 1 (2017): 41–50. http://dx.doi.org/10.17706/ijbbb.2017.7.1.41-50.

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13

MATSUBARA, Yumiko. "Gene substitutions in relation to megakaryopoiesis and thrombopoiesis." Japanese Journal of Thrombosis and Hemostasis 23, no. 6 (2012): 564–70. http://dx.doi.org/10.2491/jjsth.23.564.

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14

Gulsu, Emre, Çigdem Eresen Yazıcıoğlu, Sefa Kızıldag, Banu Değirmencioğlu, Serhat Taslıca, and Koksal Alptekin. "Poster #S136 RELATION OF RGS4 GENE WITH SCHIZOPHRENIA." Schizophrenia Research 153 (April 2014): S138. http://dx.doi.org/10.1016/s0920-9964(14)70415-3.

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15

Loos, B. G., A. Fiebig, M. Nothnagel, S. Jepsen, B. Groessner-Schreiber, A. Franke, P. M. Jervøe-Storm, K. Schenck, U. van der Velden, and S. Schreiber. "NOD1 gene polymorphisms in relation to aggressive periodontitis." Innate Immunity 15, no. 4 (July 8, 2009): 225–32. http://dx.doi.org/10.1177/1753425909103739.

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16

Li, Hong, and Michael S. Goligorsky. "Endothelial Gene Responses to Homocysteine: Relation to Atherosclerosis." Nephron Experimental Nephrology 10, no. 2 (April 5, 2002): 164–69. http://dx.doi.org/10.1159/000049911.

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17

Schumacher, G., D. Sizmann, H. Haug, P. Buckel, and A. Böck. "Penicillin acylase fromE. coli: unique gene-protein relation." Nucleic Acids Research 14, no. 14 (1986): 5713–27. http://dx.doi.org/10.1093/nar/14.14.5713.

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18

McKusick, Victor A. "The human gene map in relation to cancer." Cancer Genetics and Cytogenetics 41, no. 2 (September 1989): 215. http://dx.doi.org/10.1016/0165-4608(89)90249-5.

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19

Raafat AbdRaboh, Naglaa, Manal Louis Louka, and Inas Mohamed Sabry. "Leptin gene microsatellite polymorphism: Relation to metabolic syndrome." Gene Reports 4 (September 2016): 87–90. http://dx.doi.org/10.1016/j.genrep.2016.04.002.

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20

Karopka, Thomas, Thomas Scheel, Sven Bansemer, and Änne Glass. "Automatic construction of gene relation networks using text mining and gene expression data." Medical Informatics and the Internet in Medicine 29, no. 2 (June 2004): 169–83. http://dx.doi.org/10.1080/14639230412331280422.

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21

SENDA, MICHIHIRO. "Relation between CYP2D6 gene diagnosis and phenotyping in Japanese." Rinsho yakuri/Japanese Journal of Clinical Pharmacology and Therapeutics 30, no. 1 (1999): 81–82. http://dx.doi.org/10.3999/jscpt.30.81.

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22

Li, Zhi-Peng, Mei Zhang, Jie Gao, Guo-Yan Zhou, Shuang-Qing Li, and Zhen-Mei An. "Relation between ADIPOQ Gene Polymorphisms and Type 2 Diabetes." Genes 6, no. 3 (July 8, 2015): 512–19. http://dx.doi.org/10.3390/genes6030512.

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23

Louropoulou, Anna, Ubele van der Velden, Ton Schoenmaker, Arnold Catsburg, Paul H. M. Savelkoul, and Bruno G. Loos. "Mannose-binding lectin gene polymorphisms in relation to periodontitis." Journal of Clinical Periodontology 35, no. 11 (November 2008): 923–30. http://dx.doi.org/10.1111/j.1600-051x.2008.01311.x.

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24

Grah, Rok, and Tamar Friedlander. "The relation between crosstalk and gene regulation form revisited." PLOS Computational Biology 16, no. 2 (February 25, 2020): e1007642. http://dx.doi.org/10.1371/journal.pcbi.1007642.

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25

Klop, B., T. M. van den Berg, A. P. Rietveld, J. Chaves, J. T. Real, J. F. Ascaso, R. Carmena, J. W. F. Elte, and Manuel Castro Cabezas. "AT1 Receptor Gene Polymorphisms in relation to Postprandial Lipemia." International Journal of Vascular Medicine 2012 (2012): 1–6. http://dx.doi.org/10.1155/2012/271030.

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Background. Recent data suggest that the renin-angiotensin system may be involved in triglyceride (TG) metabolism. We explored the effect of the common A1166C and C573T polymorphisms of the angiotensin II type 1 receptor (AT1R) gene on postprandial lipemia.Methods. Eighty-two subjects measured daytime capillary TG, and postprandial lipemia was estimated as incremental area under the TG curve. The C573T and A1166C polymorphisms of the AT1R gene were determined.Results. Postprandial lipemia was significantly higher in homozygous carriers of the 1166-C allele (9.39±8.36 mM*h/L) compared to homozygous carriers of the 1166-A allele (2.02±6.20 mM*h/L) (P<0.05). Postprandial lipemia was similar for the different C573T polymorphisms.Conclusion. The 1166-C allele of the AT1R gene seems to be associated with increased postprandial lipemia. These data confirm the earlier described relationships between the renin-angiotensin axis and triglyceride metabolism.

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26

ÖSTLUND, HANNA, EVA KELLER, and YASMIN L. HURD. "Estrogen Receptor Gene Expression in Relation to Neuropsychiatric Disorders." Annals of the New York Academy of Sciences 1007, no. 1 (December 2003): 54–63. http://dx.doi.org/10.1196/annals.1286.006.

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27

Dutta, Hemonta Kr, Debasish Borbora, Mauchumi Baruah, and Kanwar Narain. "Evidence of gene-gene interactions betweenMTHFD1andMTHFRin relation to anterior encephalocele susceptibility in Northeast India." Birth Defects Research 109, no. 6 (February 20, 2017): 432–44. http://dx.doi.org/10.1002/bdra.23607.

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28

Milczarek, D., A. Przetakiewicz, P. Kamiński, and B. Flis. "Early selection of potato clones with the H1 resistance gene – the relation of nematode resistance to quality characteristics." Czech Journal of Genetics and Plant Breeding 50, No. 4 (November 27, 2014): 278–84. http://dx.doi.org/10.17221/114/2014-cjgpb.

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Breeding a new potato cultivar is a long-term process ending with a few elite individuals from initially large populations. Screening for resistance in the seedling and first clonal generations is a cost-effective and efficient way to reduce the time needed to create a new variety. Unlike the phenotypic assessment of resistance to nematodes, marker-assisted selection (MAS) can be applied at early stages of selection. The frequent question among breeders is about the impact of early selection for resistance on the agronomic value of finally selected resistant progeny. The study presents a relationship between the presence of markers TG689 and 57R and some agricultural traits in field grown seedlings and three successive vegetative generations. Both markers are linked to H1 gene, which confers resistance to the golden cyst nematode Globodera rostochiensis. Clones with these markers had higher total tuber and starch yield than those without the markers. A negative relationship between marker presence and quality was not observed.

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29

Nienaber-Rousseau, Cornelie, Suria M. Ellis, Sarah J. Moss, Alida Melse-Boonstra, and G. Wayne Towers. "Gene–environment and gene–gene interactions of specific MTHFR, MTR and CBS gene variants in relation to homocysteine in black South Africans." Gene 530, no. 1 (November 2013): 113–18. http://dx.doi.org/10.1016/j.gene.2013.07.065.

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30

Rezaei, Abolhasan, Sheyda Akhshabi, and Hamid Jamalzadeh. "The relation between growth hormone (GH) gene and Cytochrome b gene in three salmon types." Egyptian Academic Journal of Biological Sciences. C, Physiology and Molecular Biology 4, no. 1 (December 1, 2012): 133–40. http://dx.doi.org/10.21608/eajbsc.2012.16132.

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31

Berrin, Tuğrul, Yılmaz Hikmet, Vatandaş Gülşen, Bozyiğit Ferda, Balcan Erdal, and Onur Ece. "No relation between EFHC2 gene polymorphism and Idiopathic generalized epilepsy." African Health Sciences 15, no. 4 (January 18, 2016): 1204. http://dx.doi.org/10.4314/ahs.v15i4.20.

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32

Pineda Marfa, M., M. O'Callaghan Gordo, E. Gerotina Mora, E. Quandt Herrera, M. Rabaza Gairí, N. Brandi Tarrau, E. Cortès Saladelafont, A. Roche Martínez, and J. Armstrong Morón. "O42 – 1909 FOXG1 gene: phenotype–genotype relation in Spanish patients." European Journal of Paediatric Neurology 17 (September 2013): S14. http://dx.doi.org/10.1016/s1090-3798(13)70044-8.

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33

Rutter, M. "Gene—environment interplay in relation to emotional and behavioural disturbance." European Psychiatry 17 (May 2002): 13. http://dx.doi.org/10.1016/s0924-9338(02)80062-1.

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34

Liukkonen, A., Q. He, U. K. Gürsoy, P. J. Pussinen, K. Gröndahl-Yli-Hannuksela, J. Liukkonen, T. Sorsa, A. L. Suominen, S. Huumonen, and E. Könönen. "Mannose-binding lectin gene polymorphism in relation to periodontal infection." Journal of Periodontal Research 52, no. 3 (September 14, 2016): 540–45. http://dx.doi.org/10.1111/jre.12420.

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35

Rutter, Michael, and Judy Silberg. "Gene-Environment Interplay in Relation to Emotional and Behavioral Disturbance." Annual Review of Psychology 53, no. 1 (February 2002): 463–90. http://dx.doi.org/10.1146/annurev.psych.53.100901.135223.

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36

Gürkan, Ali, Gülnur Emingil, Buket Han Saygan, Gül Atilla, Timur Köse, Haluk Baylas, and Afig Berdeli. "Renin-angiotensin gene polymorphisms in relation to severe chronic periodontitis." Journal of Clinical Periodontology 36, no. 3 (March 2009): 204–11. http://dx.doi.org/10.1111/j.1600-051x.2008.01379.x.

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37

Ritland, Kermit, and Fred R. Ganders. "CROSS ABILITY OFMIMULUS GUTTATUSIN RELATION TO COMPONENTS OF GENE FIXATION." Evolution 41, no. 4 (July 1987): 772–86. http://dx.doi.org/10.1111/j.1558-5646.1987.tb05852.x.

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38

LIN, C. L., and C. P. HUNG. "Impersonation Attack on Two-Gene-Relation Password Authentication Protocol (2GR)." IEICE Transactions on Communications E89-B, no. 12 (December 1, 2006): 3425–27. http://dx.doi.org/10.1093/ietcom/e89-b.12.3425.

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39

Tekeli, Oya, M. Erol Turaçlı, Buket Altınok, Nejat Akar, and Atilla Halil Elhan. "No Relation between Angiotensin-Converting Enzyme Gene Polymorphism and Pseudoexfoliation." Ophthalmic Research 40, no. 1 (November 27, 2006): 32–34. http://dx.doi.org/10.1159/000111156.

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40

Craandijk, Jeroen, Michiel V. Van Krugten, Cor L. Verweij, Ubele Van Der Velden, and Bruno G. Loos. "Tumor necrosis factor-α gene polymorphisms in relation to periodontitis." Journal of Clinical Periodontology 29, no. 1 (January 2002): 28–34. http://dx.doi.org/10.1034/j.1600-051x.2002.290105.x.

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41

Li, Gang, Karen E. Ross, Cecilia N. Arighi, Yifan Peng, Cathy H. Wu, and K. Vijay-Shanker. "miRTex: A Text Mining System for miRNA-Gene Relation Extraction." PLOS Computational Biology 11, no. 9 (September 25, 2015): e1004391. http://dx.doi.org/10.1371/journal.pcbi.1004391.

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42

Bijma, Piter, and John A. Woolliams. "On the relation between gene flow theory and genetic gain." Genetics Selection Evolution 32, no. 1 (2000): 99. http://dx.doi.org/10.1186/1297-9686-32-1-99.

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43

Tirosh, Itay, Adina Weinberger, Dana Bezalel, Mark Kaganovich, and Naama Barkai. "On the relation between promoter divergence and gene expression evolution." Molecular Systems Biology 4, no. 1 (January 2008): 159. http://dx.doi.org/10.1038/msb4100198.

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44

van Roekel, Eeske, Maaike Verhagen, Rutger C. M. E. Engels, Luc Goossens, and Ron H. J. Scholte. "Oxytocin receptor gene (OXTR) in relation to loneliness in adolescence." Psychiatric Genetics 23, no. 5 (October 2013): 204–13. http://dx.doi.org/10.1097/ypg.0b013e328363f631.

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45

Boekholdt, S. Matthijs, Jan-Albert Kuivenhoven, G. Kees Hovingh, J. Wouter Jukema, John JP Kastelein, and Arie van Tol. "CETP gene variation: relation to lipid parameters and cardiovascular risk." Current Opinion in Lipidology 15, no. 4 (August 2004): 393–98. http://dx.doi.org/10.1097/01.mol.0000137226.54278.60.

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46

Trembath, RC, GAA Ferns, S. Li, and DJ Galton. "Glucose Transporter Gene. Relation to Non-Insulin Dependent Diabetes Mellitus." Clinical Science 73, s17 (December 1, 1987): 50P. http://dx.doi.org/10.1042/cs073050p.

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47

Khakpour, Leili, Majid Motovali Bashi, and Shirin Farivar. "Investigation on the relation of CDC25A gene and breast cancer." Clinical Biochemistry 44, no. 13 (September 2011): S204. http://dx.doi.org/10.1016/j.clinbiochem.2011.08.504.

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48

Liu, Yuexue, Huwei Song, Zongli Liu, Guibing Hu, and Shunquan Lin. "Molecular characterization of loquat EjAP1 gene in relation to flowering." Plant Growth Regulation 70, no. 3 (March 1, 2013): 287–96. http://dx.doi.org/10.1007/s10725-013-9800-0.

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49

Altaf-Ul-Amin, Md, Tetsuo Katsuragi, Tetsuo Sato, Naoaki Ono, and Shigehiko Kanaya. "An Unsupervised Approach to Predict Functional Relations between Genes Based on Expression Data." BioMed Research International 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/154594.

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This work presents a novel approach to predict functional relations between genes using gene expression data. Genes may have various types of relations between them, for example, regulatory relations, or they may be concerned with the same protein complex or metabolic/signaling pathways and obviously gene expression data should contain some clues to such relations. The present approach first digitizes the log-ratio type gene expression data ofS. cerevisiaeto a matrix consisting of 1, 0, and −1 indicating highly expressed, no major change, and highly suppressed conditions for genes, respectively. For each gene pair, a probability density mass function table is constructed indicating nine joint probabilities. Then gene pairs were selected based on linear and probabilistic relation between their profiles indicated by the sum of probability density masses in selected points. The selected gene pairs share many Gene Ontology terms. Furthermore a network is constructed by selecting a large number of gene pairs based on FDR analysis and the clustering of the network generates many modules rich with similar function genes. Also, the promoters of the gene sets in many modules are rich with binding sites of known transcription factors indicating the effectiveness of the proposed approach in predicting regulatory relations.

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50

Shin, Miyoung, Hyungmin Lee, and Munpyo Hong. "A hybrid approach to gene ranking using gene relation networks derived from literature for the identification of disease gene markers." International Journal of Data Mining and Bioinformatics 6, no. 3 (2012): 239. http://dx.doi.org/10.1504/ijdmb.2012.049250.

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