Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: EC:2.7.11.24 (mitogen-activated protein kinase)
 95,810 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

The aim of the study was to identify key long non-coding RNAs (lncRNA) and related subpathways following severe burn injuries and research their functions. The miRNA-mRNA and lncRNA-miRNA interactions were downloaded from starBase v2.0 database. In addition, mRNA-miRNA interactions were obtained from TarBase, mirTarBase, mir2Disease, miRecords (V4.0) databases. The relationships of lncRNA-miRNA-mRNA were constructed. Genes of expression profiling were intersected with mRNA and lncRNA in lncRNA-mRNA interaction. Screened mRNAs were enriched into various pathways and screened lncRNAs were embedded into candidate pathways. Wallenius approximation methods were used to calculate the false discovery rate value of each sub-pathway. Based on the results of significant sub-pathways, the related lncRNA-mRNA network was constructed. A total of 18,081 genes were obtained. The lncRNA-mRNA intersections including 835 lncRNAs, 1,749 mRNAs and 7,693 interacting pairs were constructed. The enriched mRNAs were further enriched into various candidate pathways such as ribosome biogenesis in eukaryotes. Several sub-pathways were screened, including ribosome biogenesis in eukaryotes and MAPK signaling pathway. The network of pathway-lncRNA-mRNA was constructed. Hub-genes were identified, including C14orf169 and YLPM1. Several hub-lncRNAs were obtained, including PRKAG2 antisense RNA 1 and LEF1 antisense RNA 1. Several hub-lncRNAs including C14orf169, YLPM1, TTTY15, and PCBP1-AS1 were screened. The sub-pathways regulated by these lncRNAs were identified, and functions were predicted.
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PMID:Sub-pathway analysis for severe burns injury patients: Identification of potential key lncRNAs by analyzing lncRNA-mRNA profile. 2980 46

Identification of potential novel biomarkers for heart failure was undertaken using a sub-pathway based method. To realize this goal, heart failure-relevant dataset, reference pathways, and lncRNA-miRNA-mRNA interactions were firstly recruited. Secondly, the informative pathways were extracted relying on KEGG pathways and the mRNAs in the PCC-weighted lncRNA-mRNA interactions. Thirdly, lncRNA-regulated sub-pathways were dissected after construction of condition-specific lncRNA competitively regulated pathways (LCRP). To detect crucial heart failure-relevant lncRNAs, degree analysis was conducted for all nodes within the LCRP. Ultimately, the significance of candidate sub-pathways were assessed to further identify the significant sub-pathways. There were 44 lncRNAs, 165 mRNAs and 224 co-expressed interactions. After putting the 165 mRNAs into the reference pathways, 56 informative pathways were obtained which were then embedded into undirected graphs, and 44 lncRNAs were inserted into the pathway graphs to further construct the condition-specific LCRP. According to degree distribution, 4 hub lncRNAs were selected, including ERVK13-1, YLPM1, PDXDC2P, and LINC00482. Based on the LCRP information, a total of 36 sub-pathways mediated by lncRNAs participated in 40 complete pathways. Among these 40 pathways, we mainly concentrated on the top three sub-pathways, including a sub-part of MAPK signaling pathway, an important sub-part in ErbB signaling pathway, and a part of chemokine signaling pathway. In the top 3 significant sub-pathways, gene AKT3 was simultaneously regulated by ERVK13-1, YLPM1, and PDXDC2P. Sub-pathways including MAPK signaling pathway and hub lncRNAs (ERVK13-1, YLPM1, and PDXDC2P) may play an important role in heart failure.
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PMID:Sub-pathway based approach to systematically track candidate sub-pathway biomarkers for heart failure. 3093 89