scholarly journals In silico Analysis of Transcription Factors Associated to Differentially Expressed Genes in Irradiated Glioblastoma Cell Lines

10.5772/53299 ◽  
2013 ◽  
Author(s):  
P. R. D. V. Godoy ◽  
S. S. ◽  
F. S. ◽  
E. A. ◽  
G. A. S. Passos ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Cell Lines ◽  
Differentially Expressed Genes ◽  
In Silico ◽  
In Silico Analysis ◽  
Differentially Expressed ◽  
Glioblastoma Cell ◽  
Factors Associated ◽  
Silico Analysis ◽  
Glioblastoma Cell Lines

scholarly journals A Comparative Meta-Analysis and in silico Analysis of Differentially Expressed Genes and Proteins in Canine and Human Bladder Cancer

2020 ◽  
Vol 7 ◽  
Author(s):  
Victoria Vitti Gambim ◽  
Renee Laufer-Amorim ◽  
Ricardo Henrique Fonseca Alves ◽  
Valeria Grieco ◽  
Carlos Eduardo Fonseca-Alves
Keyword(s):  
Bladder Cancer ◽  
Differentially Expressed Genes ◽  
In Silico ◽  
Meta Analysis ◽  
In Silico Analysis ◽  
Differentially Expressed ◽  
Human Bladder Cancer ◽  
Human Bladder ◽  
Silico Analysis

In silico analysis and prediction of transcription factors of the proteins interacting with astrocyte elevated gene-1

2021 ◽  
Vol 92 ◽  
pp. 107478
Author(s):  
Sushmitha Sriramulu ◽  
Suman K. Nandy ◽  
Harsha Ganesan ◽  
Antara Banerjee ◽  
Surajit Pathak
Keyword(s):  
Transcription Factors ◽  
In Silico ◽  
In Silico Analysis ◽  
Silico Analysis

scholarly journals Characterization and risk association of polymorphisms in Aurora kinases A, B and C with genetic susceptibility to gastric cancer development

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Aner Mesic ◽  
Marija Rogar ◽  
Petra Hudler ◽  
Nurija Bilalovic ◽  
Izet Eminovic ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Transcription Factors ◽  
In Silico ◽  
In Silico Analysis ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Mitotic Kinases ◽  
Genes Encoding ◽  
Silico Analysis ◽  
Control Study

Abstract Background Single nucleotide polymorphisms (SNPs) in genes encoding mitotic kinases could influence development and progression of gastric cancer (GC). Methods Case-control study of nine SNPs in mitotic genes was conducted using qPCR. The study included 116 GC patients and 203 controls. In silico analysis was performed to evaluate the effects of polymorphisms on transcription factors binding sites. Results The AURKA rs1047972 genotypes (CT vs. CC: OR, 1.96; 95% CI, 1.05–3.65; p = 0.033; CC + TT vs. CT: OR, 1.94; 95% CI, 1.04–3.60; p = 0.036) and rs911160 (CC vs. GG: OR, 5.56; 95% CI, 1.24–24.81; p = 0.025; GG + CG vs. CC: OR, 5.26; 95% CI, 1.19–23.22; p = 0.028), were associated with increased GC risk, whereas certain rs8173 genotypes (CG vs. CC: OR, 0.60; 95% CI, 0.36–0.99; p = 0.049; GG vs. CC: OR, 0.38; 95% CI, 0.18–0.79; p = 0.010; CC + CG vs. GG: OR, 0.49; 95% CI, 0.25–0.98; p = 0.043) were protective. Association with increased GC risk was demonstrated for AURKB rs2241909 (GG + AG vs. AA: OR, 1.61; 95% CI, 1.01–2.56; p = 0.041) and rs2289590 (AC vs. AA: OR, 2.41; 95% CI, 1.47–3.98; p = 0.001; CC vs. AA: OR, 6.77; 95% CI, 2.24–20.47; p = 0.001; AA+AC vs. CC: OR, 4.23; 95% CI, 1.44–12.40; p = 0.009). Furthermore, AURKC rs11084490 (GG + CG vs. CC: OR, 1.71; 95% CI, 1.04–2.81; p = 0.033) was associated with increased GC risk. A combined analysis of five SNPs, associated with an increased GC risk, detected polymorphism profiles where all the combinations contribute to the higher GC risk, with an OR increased 1.51-fold for the rs1047972(CT)/rs11084490(CG + GG) to 2.29-fold for the rs1047972(CT)/rs911160(CC) combinations. In silico analysis for rs911160 and rs2289590 demonstrated that different transcription factors preferentially bind to polymorphic sites, indicating that AURKA and AURKB could be regulated differently depending on the presence of particular allele. Conclusions Our results revealed that AURKA (rs1047972 and rs911160), AURKB (rs2241909 and rs2289590) and AURKC (rs11084490) are associated with a higher risk of GC susceptibility. Our findings also showed that the combined effect of these SNPs may influence GC risk, thus indicating the significance of assessing multiple polymorphisms, jointly. The study was conducted on a less numerous but ethnically homogeneous Bosnian population, therefore further investigations in larger and multiethnic groups and the assessment of functional impact of the results are needed to strengthen the findings.

scholarly journals A clinical and in-silico analysis of hsa-miR-21 and Growth Differentiation factor-15 expression in Diabetic Nephropathy

2021 ◽  
Author(s):  
Riddhi Girdhar Agarwal ◽  
Purvi Purohit ◽  
Manoj Khokhar ◽  
Anupama Modi ◽  
Nitin Kumar Bajpai ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Transcription Factors ◽  
In Silico ◽  
Clinical Chemistry ◽  
In Silico Analysis ◽  
Healthy Controls ◽  
Ppi Network ◽  
Renal Disorder ◽  
Stage Renal Disease ◽  
Silico Analysis

Abstract Background: Diabetic Nephropathy (DN), a microvascular complication, is a major cause of end-stage renal disease (ESRD). GDF-15 and hsa-miR-21 are closely associated with endothelial dysfunction and inflammation.Methods: In-silico analysis was used to identify GDF-15 and insulin related protein-protein interaction (PPI) network and a common set of GDF-15 regulating transcription factors. Common targeting miRNA of GDF-15 regulating transcription factors were investigated in miRNet and TargetScan. Further, 30 type 2 DN patients and 30 healthy controls were included for clinical chemistry analysis, to analyze serum GDF-15 levels by ELISA and to evaluate the fold change expression (FCE) of circulating hsa-miR-21 by RT-PCR.Results: In the PPI network of IRS1, IRS2, INSR, IGF1R, INS, AKT1, PPARG, CEBPB, EGR1, TP53, KLF4, ATF3, GDF15, TWIST2, the common nodes between insulin and GDF-15 were identified. MicroRNA-21 was bioinformatically observed to directly target GDF-15 downregulating transcription factors KLF4, TP-53, and CEBPB. Serum GDF-15 was nearly ten (10) folds higher in DN patients (p˂0.0001) as compared to healthy controls. A positive and significant correlation of serum GDF-15 was found with HbA1c, HOMA-IR, serum urea and serum creatinine. The FCE of hsa-miR-21 was 9.18 folds higher in DN patients. Conclusion: Raised serum GDF-15 and circulating hsa-miR-21 can serve as clinically important therapeutic targets and biomarkers of progressive renal disorder.

scholarly journals Drug-disease interactions of differentially expressed genes in COVID-19 liver samples: an in-silico analysis

2021 ◽  
Vol 62 (4) ◽  
pp. 316-324
Author(s):  
Susan Omar Rasool ◽  
Ata Mirzaei Nahr ◽  
Sania Eskandari ◽  
Milad Hosseinzadeh ◽  
Soheila Asoudeh Moghanloo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cytochrome P450 ◽  
Differentially Expressed Genes ◽  
In Silico ◽  
In Silico Analysis ◽  
Gene Interaction ◽  
Differentially Expressed ◽  
Alcoholic Fatty Liver ◽  
Interaction Database ◽  
Cytochrome P450 Genes

While COVID-19 liver injuries have been reported in various studies, concerns are raised about disease-drug reactions in COVID-19 patients. In this study, we examined the hypothesis of gene-disease interactions in an in-silico model of gene expression to seek changes in cytochrome P450 genes. The Gene Expression Omnibus dataset of the liver autopsy in deceased COVID-19 patients (GSE150316) was used in this study. Non-alcoholic fatty liver biopsies were used as the control (GSE167523). Besides, gene expression analysis was performed using the DESeq/EdgeR method. The GO databases were used, and the paths were set at p<0.05. The drug-gene interaction database (DGIdb) was searched for interactions. According to the results, 5,147 genes were downregulated, and 5,122 genes were upregulated in SARS-CoV-2 compared to healthy livers. Compared to the cytochromes, 34 cytochromes were downregulated, while 4 cytochromes were upregulated among the detected differentially expressed genes (DEG). The drug-gene interaction database (DGIdb) provided a list of medications with potential interactions with COVID-19 as well as metacetamol, phenethyl isocyanate, amodiaquine, spironolactone, amiloride, acenocoumarol, clopidogrel, phenprocoumon, trimipramine, phenazepam, etc. Besides, dietary compounds of isoflavones, valerian, and coumarin, as well as caffeine metabolism were shown to have possible interactions with COVID-19 disease. Our study showed that expression levels of cytochrome P450 genes could get altered following COVID-19. In addition, a drug-disease interaction list is recommended to be used for evaluations in clinical considerations in further studies.

scholarly journals In silico Analysis of Transcription Factor Repertoire and Prediction of Stress Responsive Transcription Factors in Soybean

DNA Research ◽  
2009 ◽  
Vol 16 (6) ◽  
pp. 353-369 ◽  
Author(s):  
K. Mochida ◽  
T. Yoshida ◽  
T. Sakurai ◽  
K. Yamaguchi-Shinozaki ◽  
K. Shinozaki ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
In Silico ◽  
In Silico Analysis ◽  
Silico Analysis
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