“…METHODS: High-throughput sequencing was conducted to detect the alterations in the expression of exosomal lncRNAs and mRNAs. Gene ontology (GO) functional analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to determine the significant functions and pathways associated with differentially expressed (DE) lncRNAs. …”
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“…METHODS: Databases, including The Cancer Genome Atlas, Gene Ontology Resource, University of California Santa Cruz Genome Browser, and Pubmed, were used to screen epigenetic modulators, regulators for CD8(+) T cells, and transcriptional regulators of programmed cell death‐ligand 1 (PD‐L1). …”
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“…Demographic and clinical data were recorded in detail, and peripheral blood samples were collected for whole-exome sequencing (WES). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to predict the functional effect of mutant genes. …”
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“…Subsequently, the candidate genes were screened using protein–protein interaction (PPI), gene ontology (GO) enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. …”
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“…The biological function and pathways of the TWAS genes were explored using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases, and the human cartilage mRNA expression profiles were utilized to validate the TWAS genes. …”
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“…GPER KO whole transcriptome respect to wild type (WT) MDA-MB-231 cells was determined through total RNA sequencing (RNA-Seq) and gene ontology (GO) enrichment analysis. We ascertained that anti-proliferative and pro-apoptotic gene signatures characterize GPER KO MDA-MB-231 cells. …”
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“…We categorized the collected omic data based on: i) cell type, ii) harmful agent, and iii) senescence stage (early and late senescence). By employing Gene Ontology and Network analysis on the omic data, we identified common and specific features of different senescent phenotypes. …”
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“…PtrCOBLs were found localized at the plasma membrane and extracellular matrix, while gene ontology analysis showed their involvement in plant development, plant growth, stress response, cellulose biosynthesis, and cell wall biogenesis. …”
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“…Hub genes were identified and conducted Gene ontology (GO) and pathway enrichment analysis through MCODE and Clue GO in Cytospace respectively. …”
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“…Then, bioinformatics analysis including Gene Ontology, Kyoto Encyclopedia Genes Genomes and Protein–Protein Interaction network analysis was performed. …”
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“…Using the GenePaint RNA in situ hybridization data for mouse embryos and single cell RNA sequencing (scRNAseq) data from e14.5 dissected pituitary glands, we confirmed expression for all candidate genes in the tissues that contribute to the developing pituitary gland. Using gene ontology (GO) terms associated with these 51 genes, we identified molecular pathways not previously associated with pituitary gland organogenesis, including cilia formation, amino acid metabolism, and epigenetic regulation. …”
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“…We obtained an initial set of 786 proteins that co precipitate with PROP1. Ontology enrichment analysis shows that PROP1 immunoprecipitated with several nuclear proteins related to transcriptional regulation and splicing and also with many non nuclear proteins related to cell adhesion and migration. …”
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“…Of these ASIGs, most did not show consistent maternal or paternal bias between the same tissue from different hybrids or different tissues from one hybrid cross. By gene ontology (GO) analysis, five and eight categories of GO exhibited significantly higher functional enrichments for ASIGs identified in embryo and endosperm, respectively. …”
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“…Peripheral blood mononuclear cells (PBMCs) were isolated by the Ficoll-Paque density gradient method, and differentially expressed genes (DEGs) encoding transcription factors in frailty were detected by Illumina and bioinformatics analyzed with R software. Gene Ontology (GO) enrichment analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to explore the functional roles of these DEGs and the target genes related to frailty phenotypes. …”
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“…The combined analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed that the activation, metabolism of various substances (lipids, sugars, amino acids) play a major role in restoring pollen germination capacity. …”
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“…An assessment for risk of bias was carried out using the Newcastle–Ottawa Scale and Quality Assessment of Diagnostic Accuracy Studies or the NIH quality assessment tool, and a meta-analysis was performed for replicable candidate biomarkers, i.e., consistently reported candidate biomarkers (in specific saliva samples, and periodontitis subgroups, reported in ≥2 independent cohorts/reports) were identified. A Gene Ontology enrichment analysis was conducted using the Database for Annotation, Visualization, and Integrated Discovery bioinformatics resources, which consistently expressed candidate biomarkers, to explore the predominant pathway wherein salivary biomarkers consistently manifested. …”
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“…Correlations between clinical characteristics and HtrA expression levels were then explored using a Wilcoxon rank sum test. A Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were performed using “clusterProfile” in the R software. …”
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“…RESULTS: In this study, transcriptome analysis was performed by RNA sequencing (RNA-seq), and the functions of the DE mRNAs and DE lncRNAs were predicted by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. …”
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“…Two polygenic risk scores (PRSs), one representing B cell genes and the other B cell activation genes, were calculated for each individual using risk loci for SLE in genes assigned to B cell-related pathways according to the Kyoto Encyclopedia of Genes and Genomes, Gene Ontology and Reactome Databases. RESULTS: Double-stranded DNA (dsDNA) antibodies were more prevalent among patients with a high compared with a low SLE B cell PRS (OR 1.47 (1.07 to 2.01), p=0.018), and effect sizes were augmented in patients with human leucocyte antigen (HLA) risk haplotypes HLA-DRB1*03:01 and HLA-DRB1*15:01 (DRB1*03/15 −/− (OR 0.99 (0.56 to 1.77), p=0.98; DRB1*03/15 +/− or −/+ (OR 1.64 (1.06 to 2.54), p=0.028; and DRB1*03/15 +/+ (OR 4.47 (1.21 to 16.47), p=0.024). …”
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“…Tumor mutation burden (TMB), microsatellite instability (MSI), and immune checkpoint expression in cancers were analyzed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to perform enrichment and visualization. …”
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