scholarly journals netGO: R-Shiny package for network-integrated pathway enrichment analysis

2020 ◽  
Vol 36 (10) ◽  
pp. 3283-3285
Author(s):  
Jinhwan Kim ◽  
Sora Yoon ◽  
Dougu Nam
Keyword(s):  
Target Genes ◽  
Genome Wide Association Study ◽  
Enrichment Analysis ◽  
Supplementary Information ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Pathway Gene ◽  
Gene Sets ◽  
R Shiny ◽  
Integrated Pathway

Abstract Summary We present an R-Shiny package, netGO, for novel network-integrated pathway enrichment analysis. The conventional Fisher’s exact test (FET) considers the extent of overlap between target genes and pathway gene-sets, while recent network-based analysis tools consider only network interactions between the two. netGO implements an intuitive framework to integrate both the overlap and networks into a single score, and adaptively resamples genes based on network degrees to assess the pathway enrichment. In benchmark tests for gene expression and genome-wide association study (GWAS) data, netGO captured the relevant gene-sets better than existing tools, especially when analyzing a small number of genes. Specifically, netGO provides user-interactive visualization of the target genes, enriched gene-set and their network interactions for both netGO and FET results for further analysis. For this visualization, we also developed a standalone R-Shiny package shinyCyJS to connect R-shiny and the JavaScript version of cytoscape. Availability and implementation netGO R-Shiny package is freely available from github, https://github.com/unistbig/netGO. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Mechanism of YuPingFeng in the Treatment of COPD Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yunhong Yin ◽  
Jianyu Liu ◽  
Mengyu Zhang ◽  
Rui Li ◽  
Xiao Liu ◽  
...  
Keyword(s):  
Clinical Practice ◽  
Target Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Signalling Pathways ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Herbal Formula ◽  
Pathway Enrichment ◽  
Topological Parameters

YuPingFeng (YPF) granules are a classic herbal formula extensively used in clinical practice in China for the treatment of COPD. However, the pathological mechanisms of YPF in COPD remain undefined. In the present research, a network pharmacology-based strategy was implemented to elucidate the underlying multicomponent, multitarget, and multipathway modes of action of YPF against COPD. First, we identified putative YPF targets based on TCMSP databases and constructed a network containing interactions between putative YPF targets and known therapeutic targets of COPD. Next, two topological parameters, “degree” and “closeness,” were calculated to identify target genes in the network. The major hubs were imported to the MetaCore database for pathway enrichment analysis. In total, 23 YPF active ingredients and 83 target genes associated with COPD were identified. Through protein interaction network analysis, 26 genes were identified as major hubs due to their topological importance. GO and KEGG enrichment analysis results revealed YPF to be mainly associated with the response to glucocorticoids and steroid hormones, with apoptotic and HIF-1 signalling pathways being dominant and correlative pathways. The promising utility of YPF in the treatment of COPD has been demonstrated by a network pharmacology approach.

Multiomics analysis identifies key genes and pathways related to N6-methyladenosine RNA modification in ovarian cancer

Epigenomics ◽  
2021 ◽  
Author(s):  
Haoya Xu ◽  
Xianli Li ◽  
Shengtan Wang ◽  
Feifei Li ◽  
Jian Gao ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Target Genes ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Rna Modification ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Number Variation ◽  
Cancer Genome Atlas ◽  
Patient Prognosis

Aims: To explore the pathways and target genes related to N6-methyladenosine (m6A) methylation in ovarian cancer and their effect on patient prognosis. Methods & materials: The Cancer Genome Atlas was used to screen genes related to m6A regulators in terms of gene expression, mutation and copy number variation. These genes were subjected to pathway enrichment analysis. Prognosis-related genes were screened and involved in risk signature construction. Immunohistochemistry was used for verification. Results: We obtained 1408 genes dysregulated in parallel to m6A regulators, which were mainly involved in the platelet activation pathway. The m6A-related signature was constructed based on the expression of four prognosis-related genes ( RPS6KA2, JUNB, HNF4A and P2RX1). Conclusion: This work provides new insights into the mechanism of m6A methylation in ovarian cancer.

scholarly journals Novel Biomarker MicroRNAs for Subtyping of Acute Coronary Syndrome: A Bioinformatics Approach

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Yujie Zhu ◽  
Yuxin Lin ◽  
Wenying Yan ◽  
Zhandong Sun ◽  
Zhi Jiang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Coronary Syndrome ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Pathway Enrichment Analysis ◽  
Biological Processes ◽  
Pathway Enrichment ◽  
Coronary Syndrome ◽  
Life Threatening

Acute coronary syndrome (ACS) is a life-threatening disease that affects more than half a million people in United States. We currently lack molecular biomarkers to distinguish the unstable angina (UA) and acute myocardial infarction (AMI), which are the two subtypes of ACS. MicroRNAs play significant roles in biological processes and serve as good candidates for biomarkers. In this work, we collected microRNA datasets from the Gene Expression Omnibus database and identified specific microRNAs in different subtypes and universal microRNAs in all subtypes based on our novel network-based bioinformatics approach. These microRNAs were studied for ACS association by pathway enrichment analysis of their target genes. AMI and UA were associated with 27 and 26 microRNAs, respectively, nine of them were detected for both AMI and UA, and five from each subtype had been reported previously. The remaining 22 and 21 microRNAs are novel microRNA biomarkers for AMI and UA, respectively. The findings are then supported by pathway enrichment analysis of the targets of these microRNAs. These novel microRNAs deserve further validation and will be helpful for personalized ACS diagnosis.

scholarly journals LncRNA HOTAIR promotes proliferation and inhibits apoptosis by sponging miR-214-3p in HPV16 positive cervical cancer cells

2021 ◽  
Author(s):  
Yu Zhou ◽  
Yuqing Wang ◽  
Mingying Lin ◽  
Daiqian Wu ◽  
Min Zhao
Keyword(s):  
Cervical Cancer ◽  
Cancer Cells ◽  
Signaling Pathway ◽  
Binding Sites ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Cervical Cancer Cells ◽  
Lncrna Hotair

Abstract Background Cervical cancer (CC) is one of the most common gynecological malignancies all around the world. The mechanisms of cervical carcinoma formation remain under close scrutiny. The long non-coding RNAs (lncRNA) and microRNAs (miRNAs) play important roles in controlling gene expression and promoting the development and progression of cervical cancer by acting as competitive endogenous RNA (ceRNA). However, the roles of lncRNA associated with ceRNAs in cervical carcinogenesis remains unknown. In this study, the expression of LncRNA HOTAIR was investigated in HPV16 positive cervical cancer cells, the candidate miRNAs and target genes were identified to clarify putative ceRNAs of HOTAIR/miRNA in cervical cancer cells. Methods The proliferate ability of cells was measured by CCK8 and EdU incorporation assays and cell apoptosis was analyzed by flow cytometry. The expression of HOTAIR, miR-214-3p, HPV16 E7 mRNA were detected by qRT-PCR. As for searching for the interaction between miR-214-3p and HOTAIR, the binding sites for miR-214-3p on HOTAIR was predicted by starbase v2.0 database, then dual-luciferase assay was used to verify the binding sites. In addition, Gene Ontology (GO) and protein-protein interaction (PPI) network analysis of target genes of miR-214-3p were performed with bioinformatics analysis. For potential signaling pathway regulated by miR-214-3p, we conducted pathway enrichment analysis by KEGG analysis and obtained key pathways in cervical cancer cells. Results Our results showed that the expression of HOTAIR was up-regulated, while that of miR-214-3p was down-regulated in HPV16-positive cervical cancer cells. The expression status of HPV16 E7 played an important role in regulating the expression of HOTAIR or miR-214-3p in cervical cancer cells. LncRNA HOTAIR knockdown could significantly inhibited cell proliferate ability and promote cellular apoptosis, whereas the inhibition of miR-214-3p expression partially reversed such results. Bioinformatics analysis identified 1451 genes as target genes of miR-214-3p. The Gene ontology (GO) and KEGG Pathway enrichment analysis showed that these target genes were mainly related to regulation of cell communication, protein binding, enzyme binding and transferase activity, and Wnt ligand biogenesis. Pathway enrichment analysis results showed that the predicted target genes were significantly enriched in Wnt/β-catenin signaling pathway. Finally, our results confirmed that miR-214-3p could significantly inhibit β-catenin expression in HPV16 positive cancer cells by qPCR and WB analysis. Conclusion HOTAIR could act as a ceRNA through binding to miR-214-3p, promote cell proliferation and inhibit the apoptosis of HPV16 positive cervical cancer. HOTAIR/miR-214-3p/Wnt/β-catenin signaling pathway might play important roles related with HPV16 positive cervical cancer. Our results provided a new perspective for identifying novel biomarkers for cervical cancer.

scholarly journals Investigation of candidate genes and mechanisms underlying obesity associated type 2 diabetes mellitus using bioinformatics analysis and screening of small drug molecules

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
G. Prashanth ◽  
Basavaraj Vastrad ◽  
Anandkumar Tengli ◽  
Chanabasayya Vastrad ◽  
Iranna Kotturshetti
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Pathway Enrichment ◽  
Drug Molecules

Abstract Background Obesity associated type 2 diabetes mellitus is a metabolic disorder ; however, the etiology of obesity associated type 2 diabetes mellitus remains largely unknown. There is an urgent need to further broaden the understanding of the molecular mechanism associated in obesity associated type 2 diabetes mellitus. Methods To screen the differentially expressed genes (DEGs) that might play essential roles in obesity associated type 2 diabetes mellitus, the publicly available expression profiling by high throughput sequencing data (GSE143319) was downloaded and screened for DEGs. Then, Gene Ontology (GO) and REACTOME pathway enrichment analysis were performed. The protein - protein interaction network, miRNA - target genes regulatory network and TF-target gene regulatory network were constructed and analyzed for identification of hub and target genes. The hub genes were validated by receiver operating characteristic (ROC) curve analysis and RT- PCR analysis. Finally, a molecular docking study was performed on over expressed proteins to predict the target small drug molecules. Results A total of 820 DEGs were identified between healthy obese and metabolically unhealthy obese, among 409 up regulated and 411 down regulated genes. The GO enrichment analysis results showed that these DEGs were significantly enriched in ion transmembrane transport, intrinsic component of plasma membrane, transferase activity, transferring phosphorus-containing groups, cell adhesion, integral component of plasma membrane and signaling receptor binding, whereas, the REACTOME pathway enrichment analysis results showed that these DEGs were significantly enriched in integration of energy metabolism and extracellular matrix organization. The hub genes CEBPD, TP73, ESR2, TAB1, MAP 3K5, FN1, UBD, RUNX1, PIK3R2 and TNF, which might play an essential role in obesity associated type 2 diabetes mellitus was further screened. Conclusions The present study could deepen the understanding of the molecular mechanism of obesity associated type 2 diabetes mellitus, which could be useful in developing therapeutic targets for obesity associated type 2 diabetes mellitus.

scholarly journals LncRNA HOTAIR promotes proliferation and inhibits apoptosis by sponging miR-214-3p in HPV16 positive cervical cancer cells

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yu Zhou ◽  
Yuqing Wang ◽  
Mingying Lin ◽  
Daiqian Wu ◽  
Min Zhao
Keyword(s):  
Cervical Cancer ◽  
Cancer Cells ◽  
Binding Sites ◽  
Target Genes ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Signal Pathway ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Cervical Cancer Cells

Abstract Background Cervical cancer (CC) is one of the most common gynaecological malignancies all around the world. The mechanisms of cervical carcinoma formation remain under close scrutiny. The long non-coding RNAs (lncRNA) and microRNAs (miRNAs) play important roles in controlling gene expression and promoting the development and progression of cervical cancer by acting as competitive endogenous RNA (ceRNA). However, the roles of lncRNA associated with ceRNAs in cervical carcinogenesis remains unknown. In this study, the expression of long non-coding RNA HOTAIR was investigated in HPV16 positive cervical cancer cells, the candidate miRNAs and target genes were identified to clarify putative ceRNAs of HOTAIR/miRNA in cervical cancer cells. Methods The proliferation ability of cells was measured by CCK8 and EdU incorporation assays and cell apoptosis was analyzed by flow cytometry. The expression of HOTAIR, miR-214-3p, HPV16 E7 mRNA were detected by qRT-PCR. As for searching for the interaction between miR-214-3p and HOTAIR, the binding sites for miR-214-3p on HOTAIR was predicted by starbase v2.0 database, then dual-luciferase assay was used to verify the binding sites. In addition, Gene Ontology (GO) and protein–protein interaction (PPI) network analysis of target genes of miR-214-3p were performed with bioinformatics analysis. The potential signal pathway regulated by HOTAIR/miR-214-3p was predicted by KEGG enrichment analysis and confirmed by qPCR and WB analysis in cervical cancer cells. Results Our results showed that expression of HOTAIR was up-regulated, while that of miR-214-3p was down-regulated in HPV16-positive cervical cancer cells. The expression status of HPV16 E7 played an important role in regulating expression of HOTAIR or miR-214-3p in cervical cancer cells. HOTAIR knockdown could significantly inhibited cell proliferate ability and promote cellular apoptosis, whereas the inhibition of miR-214-3p expression partially reversed such results. Bioinformatics analysis identified 1451 genes as target genes of miR-214-3p. The Gene ontology (GO) and KEGG Pathway enrichment analysis showed that these target genes were mainly related to regulation of cell communication, protein binding, enzyme binding and transferase activity, and Wnt ligand biogenesis. Pathway enrichment analysis results showed that the predicted target genes were significantly enriched in Wnt/β-catenin signaling pathway. Finally, our results confirmed that miR-214-3p could significantly inhibit β-catenin expression in HPV16 positive cancer cells by qPCR and WB analysis. Conclusion HOTAIR could act as a ceRNA through binding to miR-214-3p, promote cell proliferation and inhibit the apoptosis of HPV16 positive cervical cancer. HOTAIR/miR-214-3p/Wnt/β-catenin signal pathway might played important regulated roles in HPV16 positive cervical cancer. Our results provided new insight into defining novel biomarkers for cervical cancer.

scholarly journals Identification of Potential Genetic Biomarkers and Target Genes of Peri-Implantitis Using Bioinformatics Tools

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Xiaogen Zhang ◽  
Zhifa Wang ◽  
Li Hu ◽  
Xiaoqing Shen ◽  
Chundong Liu
Keyword(s):  
Target Genes ◽  
Kegg Pathway ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Venn Diagram ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Potential Target ◽  
Genetic Biomarkers

Objectives. To investigate potential genetic biomarkers of peri-implantitis and target genes for the therapy of peri-implantitis by bioinformatics analysis of publicly available data. Methods. The GSE33774 microarray dataset was downloaded from the Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) between peri-implantitis and healthy gingival tissues were identified using the GEO2R tool. GO enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using the DAVID database and the Metascape tool, and the results were expressed as a bubble diagram. The protein-protein interaction network of DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING) and visualized using Cytoscape. The hub genes were screened by the cytoHubba plugin of Cytoscape. The potential target genes associated with peri-implantitis were obtained from the DisGeNET database and the Open Targets Platform. The intersecting genes were identified using the Venn diagram web tool. Results. Between the peri-implantitis group and the healthy group, 205 DEGs were investigated including 140 upregulated genes and 65 downregulated genes. These DEGs were mainly enriched in functions such as the immune response, inflammatory response, cell adhesion, receptor activity, and protease binding. The results of KEGG pathway enrichment analysis revealed that DEGs were mainly involved in the cytokine-cytokine receptor interaction, pathways in cancer, and the PI3K-Akt signaling pathway. The intersecting genes, including IL6, TLR4, FN1, IL1β, CXCL8, MMP9, and SPP1, were revealed as potential genetic biomarkers and target genes of peri-implantitis. Conclusions. This study provides supportive evidence that IL6, TLR4, FN1, IL1β, CXCL8, MMP9, and SPP1 might be used as potential target biomarkers for peri-implantitis which may provide further therapeutic potentials for peri-implantitis.

scholarly journals pathfindR: An R Package for Pathway Enrichment Analysis Utilizing Active Subnetworks

2018 ◽  
Author(s):  
Ege Ulgen ◽  
Ozan Ozisik ◽  
Osman Ugur Sezerman
Keyword(s):  
Interaction Network ◽  
Enrichment Analysis ◽  
R Package ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Protein Protein Interaction ◽  
Gene Sets ◽  
User Data ◽  
Pathway Diagrams ◽  
Protein Protein Interaction Network

AbstractSummaryPathfindR is a tool for pathway enrichment analysis utilizing active subnetworks. It identifies gene sets that form active subnetworks in a protein-protein interaction network using a list of genes provided by the user. It then performs pathway enrichment analyses on the identified gene sets. Further, using the R package pathview, it maps the user data on the enriched pathways and renders pathway diagrams with the mapped genes. Because many of the enriched pathways are usually biologically related, pathfindR also offers functionality to cluster these pathways and identify representative pathways in the clusters. PathfindR is built as a stand-alone package but it can easily be integrated with other tools, such as differential expression/methylation analysis tools, for building fully automated pipelines. In this article, an overview of pathfindR is provided and an example application on a rheumatoid arthritis dataset is presented and discussed.AvailabilityThe package is freely available under MIT license at: https://github.com/egeulgen/pathfindR

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