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For microarray data, functional enrichment analysis of Gene Ontology terms was performed by Fisher's exact test using the FatiGO tool within the Babelomics suite [26].
Examination of the promoter regions of putative miRNA target genes using the FatiGO tool revealed that regulatory motifs for a small number of transcription factors including, E2F-1 (p = 6.01×10−14), KROX (p = 9.34×10−14), MAZ (p = 2.23×10−11) and PAX6 (p = 1.76×10−9) are significantly enriched in comparison to genes in the mouse genome as a whole [37].
The GO was extracted electronically using the FatiGO tool [ 28].
The ontology distribution, according to the Swiss-Prot homologous proteins, was determined using the FatiGO tool [ 28].
Gene enrichment analyses compared the distributions of GO and KEGG categories between selected lists using the FATIGO tool of the online software suite Babelomics (http://babelomics3.bioinfo.cipf.es; [ 45]).
Functional analysis of Gene Ontology (GO) terms was carried out using the FatiGO tool and gene set enrichment analysis was performed using FatiScan [ 76, 77].
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Gene Ontology annotation analysis was carried out using the Fatigo+ tool at the Babelomics website (http://babelomics.bioinfo.cipf.es) [8].
Biological processes were available for 159 of the 288 genes analyzed using the FatiGO web tool.
Using the FatiGO Compare tool, 11,235 and 12,107 features were significantly modulated in wt and IL-16−/− BMDMs, respectively.
In order to identify genes involved in biological processes and pathways related to CNS development among the 288 up-regulated genes, we performed a more advanced gene ontology analysis using the FatiGO web tool at specificity level six, as illustrated in Table 1.
Gene Ontology annotation analysis was carried out using the Fatigo+ tool at the Babelomics website [ 50].
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