Gene ontology analysis on significantly different genes was performed on the FlyMine online database (46).
Additional predicted gene targets were verified to bind Oct4 in situ, and targets were found to be enriched in several developmental and molecular processes by
gene ontology analysis.
An approach for the identification of targets specific to bone metastasis using cancer genes interactome and
gene ontology analysis
Gene ontology analysis of the genes affected across several tissues (Supplementary Fig. 8) shows enrichment for genes in the extracellular region and genes involved in nucleosome and chromatin assembly and in protein — DNA complexes.
Not exact matches
In this study,
genes identified as differentially expressed by SAM
analysis were examined for their biologic association to the
gene ontology (GO) categories [34] as defined by the GO Consortium [33].
Gene Ontology enrichment
analysis was performed using the GOStats package in R (Falcon and Gentleman, 2007) based on Setaria italica GO annotations available at Phytozome.
Functional
gene annotation was performed using dammit, Gene Ontology (GO), KOG (WebMGA) and KEGG pathway analyses (Ka
gene annotation was performed using dammit,
Gene Ontology (GO), KOG (WebMGA) and KEGG pathway analyses (Ka
Gene Ontology (GO), KOG (WebMGA) and KEGG pathway
analyses (Kaas).
The principal component
analysis revealed that aging explains ~ 16 % of protein expression variability and is associated with
Gene Ontology terms transmembrane, integral / intrinsic membrane, endoplasmic reticulum and mitochondrion.
Recent notable enhancements include user - directed submission of data, such as micropublication; genomic data curation and presentation, including additional genomes and JBrowse, respectively; new query tools, such as SimpleMine,
Gene Enrichment
Analysis; new data displays, such as the Person Lineage browser and the Summary of
Ontology - based Annotations.
Gene ontology (GO)
analysis of
genes within 250 kb of a PORE sequence revealed enrichment in processes such as transcription regulator activity (p < 0.001), sex determination (p < 0.005), insulin receptor signaling (p < 0.001), development (p < 0.0005), and protein phosphorylation (p < 0.005).
For a typical RNA - Seq project: mapping to the transcriptome including QA, expression quantification, differential expression
analysis,
gene ontology and (un --RRB- supervised classification.
Analysis of overlaps between the merged ChIP and PORE lists, and resulting
gene ontologies, were performed with WebGestalt.