ArticleBMC bioinformatics2007
A transversal approach to predict gene product networks from ontology-based similarity.
Article in BMC bioinformatics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- An investigative network analysis mapping global cancer epidemiology.Theory in biosciences = Theorie in den Biowissenschaften · 2026Article
- UFO: A tool for unifying biomedical ontology-based semantic similarity calculation, enrichment analysis and visualization.PloS one · 2020Article
- An automated pipeline for analyzing medication event reports in clinical settings.BMC medical informatics and decision making · 2018Article
- Gene Ontology Enrichment Improves Performances of Functional Similarity of Genes.Scientific reports · 2018Article
- An improved approach to infer protein-protein interaction based on a hierarchical vector space model.BMC bioinformatics · 2018Article
- NetMiner-an ensemble pipeline for building genome-wide and high-quality gene co-expression network using massive-scale RNA-seq samples.PloS one · 2018Article
- Developing a similarity searching module for patient safety event reporting system using semantic similarity measures.BMC medical informatics and decision making · 2017Article
- An improved method for functional similarity analysis of genes based on Gene Ontology.BMC systems biology · 2016Article
- OrthoClust: an orthology-based network framework for clustering data across multiple species.Genome biology · 2014Article
- HybridGO-Loc: mining hybrid features on gene ontology for predicting subcellular localization of multi-location proteins.PloS one · 2014Article
- Implications of functional similarity for gene regulatory interactions.Journal of the Royal Society, Interface · 2012Article
- Novel search method for the discovery of functional relationships.Bioinformatics (Oxford, England) · 2012Article
- Prediction and characterization of protein-protein interaction networks in swine.Proteome science · 2012Article
- Article
- Literature aided determination of data quality and statistical significance threshold for gene expression studies.BMC genomics · 2012Article
- The what, where, how and why of gene ontology--a primer for bioinformaticians.Briefings in bioinformatics · 2011Article
- IntelliGO: a new vector-based semantic similarity measure including annotation origin.BMC bioinformatics · 2010Article
- Revealing and avoiding bias in semantic similarity scores for protein pairs.BMC bioinformatics · 2010Article
- Semantic similarity in biomedical ontologies.PLoS computational biology · 2009Review
- Assessment of protein set coherence using functional annotations.BMC bioinformatics · 2008Article
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundInterpretation of transcriptomic data is usually made through a "standard" approach which consists in clustering the genes according to their expression patterns and exploiting Gene Ontology (GO) annotations within each expression cluster. This approach makes it difficult to underline functional relationships between gene products that belong to different expression clusters. To address this issue, we propose a transversal analysis that aims to predict functional networks based on a combination of GO processes and data expression.
resultsThe transversal approach presented in this paper consists in computing the semantic similarity between gene products in a Vector Space Model. Through a weighting scheme over the annotations, we take into account the representativity of the terms that annotate a gene product. Comparing annotation vectors results in a matrix of gene product similarities. Combined with expression data, the matrix is displayed as a set of functional gene networks. The transversal approach was applied to 186 genes related to the enterocyte differentiation stages. This approach resulted in 18 functional networks proved to be biologically relevant. These results were compared with those obtained through a standard approach and with an approach based on information content similarity.
conclusionComplementary to the standard approach, the transversal approach offers new insight into the cellular mechanisms and reveals new research hypotheses by combining gene product networks based on semantic similarity, and data expression.
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