ArticleBMC bioinformatics2010
IntelliGO: a new vector-based semantic similarity measure including annotation origin.
Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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25 citing papers in PubMed.
- Influence of multi-species data on gene-disease associations in substance use disorder using random walk with restart models.PloS one · 2025Article
- Assessment of GO-Based Protein Interaction Affinities in the Large-Scale Human-Coronavirus Family Interactome.Vaccines · 2023Article
- Mantis: flexible and consensus-driven genome annotation.GigaScience · 2021Article
- Handling Big Data Scalability in Biological Domain Using Parallel and Distributed Processing: A Case of Three Biological Semantic Similarity Measures.BioMed research international · 2019Article
- An automated pipeline for analyzing medication event reports in clinical settings.BMC medical informatics and decision making · 2018Article
- An improved approach to infer protein-protein interaction based on a hierarchical vector space model.BMC bioinformatics · 2018Article
- Inferring ontology graph structures using OWL reasoning.BMC bioinformatics · 2018Article
- NoGOA: predicting noisy GO annotations using evidences and sparse representation.BMC bioinformatics · 2017Article
- Developing a similarity searching module for patient safety event reporting system using semantic similarity measures.BMC medical informatics and decision making · 2017Article
- Evaluating Functional Annotations of Enzymes Using the Gene Ontology.Methods in molecular biology (Clifton, N.J.) · 2017Article
- TopoICSim: a new semantic similarity measure based on gene ontology.BMC bioinformatics · 2016Article
- A Novel Schema to Enhance Data Quality of Patient Safety Event Reports.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016Article
- The role of ontologies in biological and biomedical research: a functional perspective.Briefings in bioinformatics · 2015Article
- Automated semantic annotation of rare disease cases: a case study.Database : the journal of biological databases and curation · 2014Article
- Semantic particularity measure for functional characterization of gene sets using gene ontology.PloS one · 2014Article
- M-Finder: Uncovering functionally associated proteins from interactome data integrated with GO annotations.Proteome science · 2013Article
- Evaluation of research in biomedical ontologies.Briefings in bioinformatics · 2013Article
- Integrative relational machine-learning for understanding drug side-effect profiles.BMC bioinformatics · 2013Article
- ppiPre: predicting protein-protein interactions by combining heterogeneous features.BMC systems biology · 2013Article
- A hybrid knowledge-based and data-driven approach to identifying semantically similar concepts.Journal of biomedical informatics · 2012Article
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5 authors.
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Abstract
backgroundThe Gene Ontology (GO) is a well known controlled vocabulary describing the biological process, molecular function and cellular component aspects of gene annotation. It has become a widely used knowledge source in bioinformatics for annotating genes and measuring their semantic similarity. These measures generally involve the GO graph structure, the information content of GO aspects, or a combination of both. However, only a few of the semantic similarity measures described so far can handle GO annotations differently according to their origin (i.e. their evidence codes).
resultsWe present here a new semantic similarity measure called IntelliGO which integrates several complementary properties in a novel vector space model. The coefficients associated with each GO term that annotates a given gene or protein include its information content as well as a customized value for each type of GO evidence code. The generalized cosine similarity measure, used for calculating the dot product between two vectors, has been rigorously adapted to the context of the GO graph. The IntelliGO similarity measure is tested on two benchmark datasets consisting of KEGG pathways and Pfam domains grouped as clans, considering the GO biological process and molecular function terms, respectively, for a total of 683 yeast and human genes and involving more than 67,900 pair-wise comparisons. The ability of the IntelliGO similarity measure to express the biological cohesion of sets of genes compares favourably to four existing similarity measures. For inter-set comparison, it consistently discriminates between distinct sets of genes. Furthermore, the IntelliGO similarity measure allows the influence of weights assigned to evidence codes to be checked. Finally, the results obtained with a complementary reference technique give intermediate but correct correlation values with the sequence similarity, Pfam, and Enzyme classifications when compared to previously published measures.
conclusionsThe IntelliGO similarity measure provides a customizable and comprehensive method for quantifying gene similarity based on GO annotations. It also displays a robust set-discriminating power which suggests it will be useful for functional clustering. AVAILABILITY: An on-line version of the IntelliGO similarity measure is available at: http://bioinfo.loria.fr/Members/benabdsi/intelligo_project/
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