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Simwos: Improving Semantic Similarity Between Gene Ontology Terms Based On Pfam Clans And Pathway Analysis
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| Author:
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ANOOJA ALI, VISHWANATH R HULIPALLED, S.S.PATIL
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| Abstract:
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Gene ontology (GO) is a dynamic vocabulary that describes the functions of genes and proteins. GO captures gene functionality at molecular level, cellular component and biological process. The extensive use of gene annotations increased the significance of semantic similarity. Several semantic similarity measures are available in literature focusing on different strategies- external corpora, topology based approaches focusing on edges, ancestor or child nodes, distance based approaches at term level and gene product level. We assume that the consolidation of all these aspects contribute a systematic measure for estimating the similarity among GO annotation entities. GO terms and the biological pathways are thoroughly studied and we developed a semantic similarity measure,SimWOS. SimWOS consider semantics concealed in ontology or the information content of term, membership of terms in fuzzy clustering,topology based similarity measure. Positive and negative dataset are created from UniProt. For comparison, we considered four published GO based semantic similarity measures based on Protein Family(Pfam)domain group similarity, Pearson’s correlation coefficient and semantic similarity. Experimental results exhibit the supremacy of SimWOS over other semantic similarity measures.
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| Keyword:
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Annotation, Fuzzy Clustering, Gene Ontology, Information Content, Semantic Similarity
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| EOI:
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| DOI:
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https://doi.org/10.31838/ijpr/2020.12.04.598
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| Download:
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