Enrichment Analysis of miRNA Targets

2012 ◽  
pp. 91-103 ◽  
Author(s):  
Jianzhen Xu ◽  
Chi-Wai Wong
Keyword(s):  
Enrichment Analysis ◽  
Mirna Targets

scholarly journals An ensemble method to predict target genes and pathways in uveal melanoma

2018 ◽  
Vol 13 (1) ◽  
pp. 90-96
Author(s):  
Chao Wei ◽  
Lei Wang ◽  
Han Zhang
Keyword(s):  
Uveal Melanoma ◽  
Target Genes ◽  
Pearson Correlation ◽  
Correlation Method ◽  
Enrichment Analysis ◽  
Ensemble Method ◽  
Borda Count ◽  
Pathway Enrichment Analysis ◽  
Mirna Targets ◽  
The Ensemble Method

AbstractObjectiveThis work proposes to predict target genes and pathways for uveal melanoma (UM) based on an ensemble method and pathway analyses. Methods: The ensemble method integrated a correlation method (Pearson correlation coefficient, PCC), a causal inference method (IDA) and a regression method (Lasso) utilizing the Borda count election method. Subsequently, to validate the performance of PIL method, comparisons between confirmed database and predicted miRNA targets were performed. Ultimately, pathway enrichment analysis was conducted on target genes in top 1000 miRNA-mRNA interactions to identify target pathways for UM patients. Results: Thirty eight of the predicted interactions were matched with the confirmed interactions, indicating that the ensemble method was a suitable and feasible approach to predict miRNA targets. We obtained 50 seed miRNA-mRNA interactions of UM patients and extracted target genes from these interactions, such as ASPG, BSDC1 and C4BP. The 601 target genes in top 1,000 miRNA-mRNA interactions were enriched in 12 target pathways, of which Phototransduction was the most significant one. Conclusion: The target genes and pathways might provide a new way to reveal the molecular mechanism of UM and give hand for target treatments and preventions of this malignant tumor.

A Method of Pathway Enrichment Analysis Based Gene Expression Variability

2013 ◽  
Vol 40 (12) ◽  
pp. 1256
Author(s):  
XiaoDong JIA ◽  
XiuJie CHEN ◽  
Xin WU ◽  
JianKai XU ◽  
FuJian TAN ◽  
...  
Keyword(s):  
Gene Expression ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Expression Variability ◽  
Pathway Enrichment

Unraveling the action mechanism of Buyang Huanwu Tang (BYHWT) for Cerebral Ischemia by Systematic Pharmacological Methodology

2020 ◽  
Vol 23 ◽  
Author(s):  
Shi-tang Ma ◽  
Ning Zhang ◽  
Ge Hong ◽  
Cheng-tao Feng ◽  
Sheng-wei Hong ◽  
...  
Keyword(s):  
Cerebral Ischemia ◽  
Virtual Screening ◽  
Signaling Pathways ◽  
Bioactive Compounds ◽  
Enrichment Analysis ◽  
Material Base ◽  
Lead Discovery ◽  
Binding Effect ◽  
Bioactive Ingredients ◽  
Compound Target

Background: Buyang Huanwu Tang (BYHWT) and relevant Traditional Chinese medicine (TCM) has its unique advantages in the treatment of cerebral ischemia. However, its pharmacological mechanism have not been fully explained. Objective: Base on the multi-component, also the entire disease network targets, the present study set out to identify major bioactive ingredients, key disease targets, and pathways of BYHWT against cerebral ischemia disease by systematic pharmacological methodology. Methods: Both the bioactive compounds from the BYHWT and the positive drugs against cerebral ischemia were fully investigated. The binding targets of the positive drugs were then obtained. A virtual screening protocol was then used to highlight the compound-target interaction. And network was constructed to visual the compound-target binding effect after docking analysis. Moreover，the targets enrichment analysis for biological processes and pathways were revealed to further explore the function of bio-targets protein gene and its role in the signal pathway. Results: A total of 382 active ingredients of the BYHWT and 23 candidate disease targets were identified. Virtual screening results indicated that multiple bioactive compounds targeted multiple proteins. Each compounds act on one or more targets. The mechanisms were linked to 20 signaling pathways, and the key mechanism was related to serotonergic synapse, calcium signaling pathway and camp signaling pathways. Conclusion: The present study explored the bioactive ingredients and mechanisms of BYHWT against cerebral ischemia by systematic pharmacological methodology. the novel methodology would provide a reference for the lead discovery of precursors, disease mechanism and material base for TCM.

Identification of Candidate Genetic Markers and a Novel 4-genes Diagnostic Model in Osteoarthritis through Integrating Multiple Microarray Data

2020 ◽  
Vol 23 (8) ◽  
pp. 805-813
Author(s):  
Ai Jiang ◽  
Peng Xu ◽  
Zhenda Zhao ◽  
Qizhao Tan ◽  
Shang Sun ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Microarray Data ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Functional Enrichment ◽  
Joint Disease ◽  
Support Vector ◽  
Diagnostic Model ◽  
Data Sets

Background: Osteoarthritis (OA) is a joint disease that leads to a high disability rate and a low quality of life. With the development of modern molecular biology techniques, some key genes and diagnostic markers have been reported. However, the etiology and pathogenesis of OA are still unknown. Objective: To develop a gene signature in OA. Method: In this study, five microarray data sets were integrated to conduct a comprehensive network and pathway analysis of the biological functions of OA related genes, which can provide valuable information and further explore the etiology and pathogenesis of OA. Results and Discussion: Differential expression analysis identified 180 genes with significantly expressed expression in OA. Functional enrichment analysis showed that the up-regulated genes were associated with rheumatoid arthritis (p < 0.01). Down-regulated genes regulate the biological processes of negative regulation of kinase activity and some signaling pathways such as MAPK signaling pathway (p < 0.001) and IL-17 signaling pathway (p < 0.001). In addition, the OA specific protein-protein interaction (PPI) network was constructed based on the differentially expressed genes. The analysis of network topological attributes showed that differentially upregulated VEGFA, MYC, ATF3 and JUN genes were hub genes of the network, which may influence the occurrence and development of OA through regulating cell cycle or apoptosis, and were potential biomarkers of OA. Finally, the support vector machine (SVM) method was used to establish the diagnosis model of OA, which not only had excellent predictive power in internal and external data sets (AUC > 0.9), but also had high predictive performance in different chip platforms (AUC > 0.9) and also had effective ability in blood samples (AUC > 0.8). Conclusion: The 4-genes diagnostic model may be of great help to the early diagnosis and prediction of OA.

Systematic Investigation of Quercetin for Treating Cardiovascular Disease Based on Network Pharmacology

2019 ◽  
Vol 22 (6) ◽  
pp. 411-420 ◽  
Author(s):  
Xian-Jun Wu ◽  
Xin-Bin Zhou ◽  
Chen Chen ◽  
Wei Mao
Keyword(s):  
Cardiovascular Disease ◽  
Cardiovascular Diseases ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Therapeutic Effects ◽  
Pathway Enrichment ◽  
Compound Target

Aim and Objective: Cardiovascular disease is a serious threat to human health because of its high mortality and morbidity rates. At present, there is no effective treatment. In Southeast Asia, traditional Chinese medicine is widely used in the treatment of cardiovascular diseases. Quercetin is a flavonoid extract of Ginkgo biloba leaves. Basic experiments and clinical studies have shown that quercetin has a significant effect on the treatment of cardiovascular diseases. However, its precise mechanism is still unclear. Therefore, it is necessary to exploit the network pharmacological potential effects of quercetin on cardiovascular disease. Materials and Methods: In the present study, a novel network pharmacology strategy based on pharmacokinetic filtering, target fishing, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, compound-target-pathway network structured was performed to explore the anti- cardiovascular disease mechanism of quercetin. Results:: The outcomes showed that quercetin possesses favorable pharmacokinetic profiles, which have interactions with 47 cardiovascular disease-related targets and 12 KEGG signaling pathways to provide potential synergistic therapeutic effects. Following the construction of Compound-Target-Pathway (C-T-P) network, and the network topological feature calculation, we obtained top 10 core genes in this network which were AKT1, IL1B, TNF, IL6, JUN, CCL2, FOS, VEGFA, CXCL8, and ICAM1. KEGG pathway enrichment analysis. These indicated that quercetin produced the therapeutic effects against cardiovascular disease by systemically and holistically regulating many signaling pathways, including Fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, MAPK signaling pathway, IL-17 signaling pathway and PI3K-Akt signaling pathway.

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