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This regulatory network was inferred from the input dataset. The miRNAs and mRNAs are presented as round and rectangle nodes respectively. The numerical value popped up upon mouse over the gene node is the log2 transformed fold-change of the gene expression between the two groups. All of the nodes are clickable, and the detailed information of the miRNAs/mRNAs and related cancer pathway will be displayed in another window. The edges between nodes are supported by both interactions (predicted or experimentally verified) and correlations learnt from cancer dataset. The numerical value popped up upon mouse over the edge is the correlation beat value (effect size) between the two nodes. The experimental evidences of the edges reported in previous cancer studies are highlighted by red/orange color. All of these information can be accessed by the "mouse-over" action. This network shows a full map of the miRNA-mRNA regulation of the input gene list(s), and the hub miRNAs (with the high network degree/betweenness centrality) would be the potential cancer drivers or tumor suppressors. The full result table can be accessed in the "Regulations" tab.

"miRNACancerMAP" is also a network visualization tool for users to draw their regulatory network by personal customization. Users can set the complexity of the network by limiting the number of nodes or edges. And the color of the nodes can be defined by different categories of the mRNAs and miRNAs, such as Gene-Ontology, pathway, and expression status. Users can also select to use network degree or network betweenness centrality to define the node size. And edges can be black or colored by the correlation. Purple edge means negative correlation (mostly found between miRNA and mRNA), and blue edge means positive correlation (found in PPI or miRNA-miRNA sponge effect). We can also add the protein-protein interactions (PPI) into the network. This result will show the cluster of genes regulated by some specific miRNAs. Additionally, miRNA-miRNA edges can be added by the "miRNA sponge" button, presenting some clusters of miRNAs that have the interactions via sponge effect.

miRNA-gene regulations

(Download full result)

Num microRNA           Gene miRNA log2FC miRNA pvalue Gene log2FC Gene pvalue Interaction Correlation beta Correlation P-value PMID Reported in cancer studies
1 hsa-miR-26a-5p CCNE2 -0.96 0 2.02 0 miRTarBase -0.49 0 24116110; 21901171 The loss of miR 26a mediated post transcriptional regulation of cyclin E2 in pancreatic cancer cell proliferation and decreased patient survival; The in vitro and in vivo assays showed that overexpression of miR-26a resulted in cell cycle arrest inhibited cell proliferation and decreased tumor growth which was associated with cyclin E2 downregulation;We also show that enforced expression of miR-26a in AML cells is able to inhibit cell cycle progression by downregulating cyclin E2 expression
2 hsa-miR-145-5p CDK4 -1.48 0 0.67 0 miRTarBase -0.15 0 21092188 Furthermore we found that CDK4 was regulated by miR-145 in cell cycle control
3 hsa-miR-195-5p CDK4 -1.86 0 0.67 0 miRTarBase -0.18 0 NA
4 hsa-let-7a-5p FBXO32 -0.33 0.00046 1.5 0 TargetScan -0.41 0.00058 NA
5 hsa-let-7c-5p HMGA2 -1.71 0 1.12 0.01594 miRTarBase -0.68 0 NA
6 hsa-let-7b-5p NRAS -0.96 0 0.3 0.00029 miRTarBase -0.11 9.0E-5 20607356 Transfection of let-7 miRNA reduced expression of pan-RAS N-RAS and K-RAS in the glioblastoma cells
NumGOOverlapSizeP ValueAdj. P Value
NumGOOverlapSizeP ValueAdj. P Value
NumGOOverlapSizeP ValueAdj. P Value

Over-represented Pathway

NumPathwayPathviewOverlapSizeP ValueAdj. P Value
1 Cellular_senescence_hsa04218 3 160 4.966e-06 0.0002582
2 PI3K_Akt_signaling_pathway_hsa04151 3 352 5.266e-05 0.001369
3 p53_signaling_pathway_hsa04115 2 68 0.0001132 0.001961
4 Cell_cycle_hsa04110 2 124 0.0003767 0.004438
5 FoxO_signaling_pathway_hsa04068 2 132 0.0004267 0.004438

Quest ID: bdc9ad09b18bd5ca1eebdd7f962f18a4