ArticleScientific reports2022
GOntoSim: a semantic similarity measure based on LCA and common descendants.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Adaptive molecular convergence is pervasive across deep time and largely decoupled from phenotypic convergence.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- An epidemiological knowledge graph extracted from the World Health Organization's Disease Outbreak News.Scientific data · 2025Article
- A multi-objective evolutionary algorithm for detecting protein complexes in PPI networks using gene ontology.Scientific reports · 2025Article
- DNA Methylation Biomarker Discovery for Colorectal Cancer Diagnosis Assistance Through Integrated Analysis.Cancer informatics · 2025Article
- Integrative bioinformatics analysis to identify ferroptosis-related genes in non-obstructive azoospermia.Journal of assisted reproduction and genetics · 2024Article
- Integrative bioinformatics analysis to identify novel biomarkers associated with non-obstructive azoospermia.Frontiers in immunology · 2023Article
- Integrative analyses of potential biomarkers and pathways for non-obstructive azoospermia.Frontiers in genetics · 2022Article
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2 authors.
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Abstract
The Gene Ontology (GO) is a controlled vocabulary that captures the semantics or context of an entity based on its functional role. Biomedical entities are frequently compared to each other to find similarities to help in data annotation and knowledge transfer. In this study, we propose GOntoSim, a novel method to determine the functional similarity between genes. GOntoSim quantifies the similarity between pairs of GO terms, by taking the graph structure and the information content of nodes into consideration. Our measure quantifies the similarity between the ancestors of the GO terms accurately. It also takes into account the common children of the GO terms. GOntoSim is evaluated using the entire Enzyme Dataset containing 10,890 proteins and 97,544 GO annotations. The enzymes are clustered and compared with the Gold Standard EC numbers. At level 1 of the EC Numbers for Molecular Function, GOntoSim achieves a purity score of 0.75 as compared to 0.47 and 0.51 GOGO and Wang. GOntoSim can handle the noisy IEA annotations. We achieve a purity score of 0.94 in contrast to 0.48 for both GOGO and Wang at level 1 of the EC Numbers with IEA annotations. GOntoSim can be freely accessed at ( http://www.cbrlab.org/GOntoSim.html ).
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.