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Interaction networks were combined with gene ontology (GO) annotation for both molecular function and biological process to identify functional clusters using the ClueGO plugin (Bindea et al., 2009).
To demonstrate the advantages of InteGO2, we computed the gene similarity scores for all the human, Arabidopsis and yeast genes on both molecular function and biological process GO categories, and generated a functional association map for each organism.
Since InteGO2 computes gene-to-gene similarities more accurately than the tested existing measures, we computed the gene similarity scores for all the human, Arabidopsis and yeast genes on both molecular function and biological process GO categories, and generated a functional association map for each organism.
To build functional classes from GO terms, we flatten the GO hierarchies for both molecular function and biological process to three levels below the tree root, and map all GO terms up to this level.
The trend stands true for both Molecular Function and Cellular Component (data not shown).
Enriched GO terms in both Molecular Function and Biological Process tended to be quite distinct in different gene sets.
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Analysis of the relative representations of both molecular functions and biological processes reveals particular trends in the cancer gene group compared to the human genome.
These molecular changes appear to result in innovations, both in molecular function and in the specialization of the reproductive axis, specifically the ability to act as an endocrine antagonist.
However, both the molecular function and the disease relevance of the spliced lncRNA 116HG are unknown.
GO analysis revealed both the molecular function and biological process of the differentially expressed proteins (Graph S1).
However, it can be seen that in both experiments (Molecular Function and Biological Process Ontology) poor values were obtained compared with the other genome predictions in the case of M. mycoides.
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