“…Differentially expressed genes were further subjected to gene ontology and pathway analyses, and their expression profiles and associations with disease parameters and outcomes were examined in clinical samples. …”
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“…We partitioned the network and identified 156 novel modules related to immune functions. Gene Ontology (GO) enrichment analyses provided insight into the key biological processes involved in determining finely tuned immune responses. …”
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“…Furthermore, a total of 1,446 target genes within the validated miRNAs were revealed using combined three bioinformatic algorithms. Analysis of Gene Ontology (GO) categories and KEGG pathways of the predicted targets revealed that carnitine supplementation regulates miRNAs that target a large set of genes involved in protein-localization and -transport, regulation of transcription and RNA metabolic processes, as well as genes involved in several signal transduction pathways, like ubiquitin-mediated proteolysis and longterm depression, are targeted by the miRNAs regulated by carnitine supplementation. …”
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“…A total of 1470 phosphorylation sites in 950 phosphoproteins were identified, and these phosphoproteins were implicated in various molecular functions and basic cellular processes by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. …”
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“…We found a total of 886 genes located within these CNVRs, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses showed they could play various roles in a number of biological processes. …”
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“…Finally, we created gene sets based on metabolic pathways annotated in the KEGG database and Gene Ontology terms associated with gene annotations available at http://www.toxodb.org. …”
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“…The intracellular biological function of the mutated genes identified by gene ontology analysis suggests a driving role in the clinicopathological characteristics of IMPC. …”
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“…RESULTS: Using all genes differentially expressed over time in RA-SFBs for any stimulus, and selecting the genes belonging to the most significant gene ontology (GO) term, i.e., ‘cartilage development’, a dynamic, robust, moderately complex multi-stimuli GRN was generated with 24 genes and 57 edges in total, 31 of which were gene-to-gene edges. …”
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“…Some identified QTL regions harbor genes known to have large effects on a variety of traits in cattle such as PLAG1 and MSTN and others harbor promising candidate genes including NCAPG, ARRDC3, ERGIC1, SH3PXD2B, HMGA2, MSRB3, LEMD3, TIGAR, SEPT7, and KIRREL3. Gene ontology analysis revealed that genes involved in ossification and in adipose tissue development were over-represented in the identified pleiotropic QTL. …”
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“…The up-regulated miRNAs were composed of miR-344, miR-346, miR-99a, miR-127, miR-128b, miR-135b, and miR-30a/b. Gene ontology and functional annotation analyses indicated that up-regulated mRNAs, such as Apc, Timp1, and Sod2, were involved in the regulation of apoptosis. …”
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“…RNA-seq was performed to identify differentially expressed genes, and gene ontology and pathways based analysis were used to identify the distinct roles of IL-2 and IL-15 in CIK preparation. …”
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“…These transcript tags were annotated with gene ontology (GO) terms. One of the most striking results from the expression analysis was that the drought sensitive plants were characterised by having approximately twice the number of differentially expressed transcript tags than the tolerant plants after drought. …”
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“…However, a number of commonly affected biological pathways, such as carbohydrate metabolism and interferon response related signaling, were revealed by gene ontology analysis. Integration of transcriptome profiling, bioinformatic algorithms, and databases of protein-protein interactome from the ENCODE project identified different nodes of GRNs utilized by miR-K12-11 in a tissue-specific fashion. …”
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“…These DEGs were associated with known gene ontology functions such as generation of precursor metabolites and energy, carbohydrate metabolic process and cellular homeostasis. …”
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“…When comparing non-irradiated and irradiated samples, we detected a time-dependent increase in differentially expressed mRNAs and miRNAs, with the highest differences detectable 20 hours after exposure. Gene ontology analysis revealed that very early events (up to 4 hours) after irradiation were specifically associated with p53 signaling and apoptotic pathways, whereas a large number of diverse cellular processes were deregulated after 20 hours. …”
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“…A total of 21,262 assembled transcripts (11,947 assembled genes) were annotated with at least one well-defined Gene Ontology (GO) and 5,131 assembled transcripts (3,181 assembled unigenes) were assigned to 329 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. …”
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“…Furthermore, we constructed an mRNA panel of PNP, AQP7 and PSMD2 (PAP panel) by logistic regression model, and evaluated the PAP panel to distinguish DHAS from LDSDS by area under the receiver operating characteristic curve (AUC) analysis, which showed a higher accuracy (AUC = 0.835). Gene ontology (GO) analysis indicated that the DHAS is most likely related to system process while the functions overrepresented by LDSDS most related to the response to stimulus. …”
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“…Candidate genes within windows that explained more than 1% of genetic variance were selected by putative function based on DAVID and Gene Ontology. RESULTS: Thirty-six QTL (1-Mb SNP window) were identified on chromosomes 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 14, 15, 16, 18, 19, 20, 21, 22, 24, 25 and 26 (UMD 3.1). …”
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“…Absence of trastuzumab as part of adjuvant therapy was the only clinical factor associated with long-term survival. Gene ontology analysis demonstrated that PI3K pathway was associated with poor response to trastuzumab-based therapy: tumours in the control group usually had four or five alterations in this pathway, whereas tumours in the Long-HER group had two alterations at most. …”
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“…A literature review and Gene Ontology analysis indicated that a significant proportion of the network genes play a role in extracellular matrix organization and skeletogenesis, and motif enrichment analysis of conserved noncoding regions of network candidates predicted a handful of transcription factors, including Ap1 and Ets2, as potential regulators of the gene network. …”
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