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NcPath: A novel tool for visualization and enrichment analysis of human non-coding RNA and KEGG signaling pathways (preprint)
biorxiv; 2022.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2022.06.03.494777
ABSTRACT
Noncoding RNAs play important roles in transcriptional processes and participate in the regulation of various biological functions, in particular miRNAs and lncRNAs. Despite their importance for several biological functions, the existing signaling pathway databases do not include information on miRNA and lncRNA. Here, we redesigned a novel pathway database named NcPath by integrating and visualizing a total of 178,308 human experimentally-validated miRNA-target interactions (MTIs), 36,537 experimentally-verified lncRNA target interactions (LTIs), and 4,879 experimentally-validated human ceRNA networks across 222 KEGG pathways (including 27 sub-categories). To expand the application potential of the redesigned NcPath database, we identified 553,523 reliable lncRNA-PCG interaction pairs by integrating co-expression relations, ceRNA relations, co-TF-binding interactions, co-Histone-modification interactions, cis-regulation relations and lncPro Tool predictions between lncRNAs and protein-coding genes. In addition, to determine the pathways in which miRNA/lncRNA targets are involved, we performed a KEGG enrichment analysis using an hypergeometric test. The NcPath database also provides information on MTIs/LTIs/ceRNA networks, PubMed IDs, gene annotations and the experimental verification method used. In summary, the NcPath database will serve as an important and continually updated platform that provides annotation and visualization of the pathways on which noncoding RNAs (miRNA and lncRNA) are involved, and provide support to multimodal noncoding RNAs enrichment analysis. The NcPath database is freely accessible at http//ncpath.pianlab.cn/.

Full text: Available Collection: Preprints Database: bioRxiv Language: English Year: 2022 Document Type: Preprint

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Full text: Available Collection: Preprints Database: bioRxiv Language: English Year: 2022 Document Type: Preprint