ArticleBioMed research international2013
Information content-based gene ontology semantic similarity approaches: toward a unified framework theory.
Article in BioMed research international, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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27 citing papers in PubMed.
- A module-based approach for post-omics, post-GWAS network-based gene classification.Bioinformatics (Oxford, England) · 2026Article
- Functional Interpretation of Omics Data: From Pathways to Networks.Advances in experimental medicine and biology · 2026Review
- Structural Changes in Gene Ontology Reveal Modular and Complex Representations of Biological Function.Molecular biology and evolution · 2025Article
- Adjustment ofFrontiers in genetics · 2023Article
- HiG2Vec: hierarchical representations of Gene Ontology and genes in the Poincaré ball.Bioinformatics (Oxford, England) · 2021Article
- Automated generation of gene summaries at the Alliance of Genome Resources.Database : the journal of biological databases and curation · 2020Article
- ViSEAGO: a Bioconductor package for clustering biological functions using Gene Ontology and semantic similarity.BioData mining · 2019Article
- GOGO: An improved algorithm to measure the semantic similarity between gene ontology terms.Scientific reports · 2018Article
- Gene Ontology Enrichment Improves Performances of Functional Similarity of Genes.Scientific reports · 2018Article
- Co-complex protein membership evaluation using Maximum Entropy on GO ontology and InterPro annotation.Bioinformatics (Oxford, England) · 2018Article
- A new method for evaluating the impacts of semantic similarity measures on the annotation of gene sets.PloS one · 2018Article
- A post-gene silencing bioinformatics protocol for plant-defence gene validation and underlying process identification: case study of the Arabidopsis thaliana NPR1.BMC plant biology · 2017Article
- Exploring Approaches for Detecting Protein Functional Similarity within an Orthology-based Framework.Scientific reports · 2017Article
- The effects of shared information on semantic calculations in the gene ontology.Computational and structural biotechnology journal · 2017Article
- SGFSC: speeding the gene functional similarity calculation based on hash tables.BMC bioinformatics · 2016Article
- Missing gene identification using functional coherence scores.Scientific reports · 2016Article
- A visual and curatorial approach to clinical variant prioritization and disease gene discovery in genome-wide diagnostics.Genome medicine · 2016Article
- A-DaGO-Fun: an adaptable Gene Ontology semantic similarity-based functional analysis tool.Bioinformatics (Oxford, England) · 2016Article
- Dissecting the Origin of Breast Cancer Subtype Stem Cell and the Potential Mechanism of Malignant Transformation.PloS one · 2016Article
- Categorizer: a tool to categorize genes into user-defined biological groups based on semantic similarity.BMC genomics · 2014Article
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2 authors.
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Abstract
Several approaches have been proposed for computing term information content (IC) and semantic similarity scores within the gene ontology (GO) directed acyclic graph (DAG). These approaches contributed to improving protein analyses at the functional level. Considering the recent proliferation of these approaches, a unified theory in a well-defined mathematical framework is necessary in order to provide a theoretical basis for validating these approaches. We review the existing IC-based ontological similarity approaches developed in the context of biomedical and bioinformatics fields to propose a general framework and unified description of all these measures. We have conducted an experimental evaluation to assess the impact of IC approaches, different normalization models, and correction factors on the performance of a functional similarity metric. Results reveal that considering only parents or only children of terms when assessing information content or semantic similarity scores negatively impacts the approach under consideration. This study produces a unified framework for current and future GO semantic similarity measures and provides theoretical basics for comparing different approaches. The experimental evaluation of different approaches based on different term information content models paves the way towards a solution to the issue of scoring a term's specificity in the GO DAG.
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