ArticleBioinformatics (Oxford, England)2010
Improving disease gene prioritization using the semantic similarity of Gene Ontology terms.
Article in Bioinformatics (Oxford, England), 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.
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Who cites it
51 citing papers in PubMed.
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- A novel candidate disease gene prioritization method using deep graph convolutional networks and semi-supervised learning.BMC bioinformatics · 2022Article
- Deepening the knowledge of rare diseases dependent on angiogenesis through semantic similarity clustering and network analysis.Briefings in bioinformatics · 2022Article
- Evaluating semantic similarity methods for comparison of text-derived phenotype profiles.BMC medical informatics and decision making · 2022Article
- HESML: a real-time semantic measures library for the biomedical domain with a reproducible survey.BMC bioinformatics · 2022Article
- Recent advances in machine learning methods for predicting LncRNA and disease associations.Frontiers in cellular and infection microbiology · 2022Review
- BiGAN: LncRNA-disease association prediction based on bidirectional generative adversarial network.BMC bioinformatics · 2021Article
- Platelet and Haemostasis are the Main Targets in Severe Cases of COVID-19 Infection; a System Biology Study.Archives of academic emergency medicine · 2021Article
- Low-Level Laser Therapy Effects on Rat Blood Hemostasis Via Significant Alteration in Fibrinogen and Plasminogen Expression Level.Journal of lasers in medical sciences · 2021Article
- LLCLPLDA: a novel model for predicting lncRNA-disease associations.Molecular genetics and genomics : MGG · 2019Article
- The utility of phenomics in diagnosis of inherited metabolic disorders.Clinical medicine (London, England) · 2019Review
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- Gene Ontology Enrichment Improves Performances of Functional Similarity of Genes.Scientific reports · 2018Article
- MGOGP: a gene module-based heuristic algorithm for cancer-related gene prioritization.BMC bioinformatics · 2018Article
- Article
- Refine gene functional similarity network based on interaction networks.BMC bioinformatics · 2017Article
- Constructing an integrated gene similarity network for the identification of disease genes.Journal of biomedical semantics · 2017Article
- NoGOA: predicting noisy GO annotations using evidences and sparse representation.BMC bioinformatics · 2017Article
- GLADIATOR: a global approach for elucidating disease modules.Genome medicine · 2017Article
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
motivationMany hereditary human diseases are polygenic, resulting from sequence alterations in multiple genes. Genomic linkage and association studies are commonly performed for identifying disease-related genes. Such studies often yield lists of up to several hundred candidate genes, which have to be prioritized and validated further. Recent studies discovered that genes involved in phenotypically similar diseases are often functionally related on the molecular level.
resultsHere, we introduce MedSim, a novel approach for ranking candidate genes for a particular disease based on functional comparisons involving the Gene Ontology. MedSim uses functional annotations of known disease genes for assessing the similarity of diseases as well as the disease relevance of candidate genes. We benchmarked our approach with genes known to be involved in 99 diseases taken from the OMIM database. Using artificial quantitative trait loci, MedSim achieved excellent performance with an area under the ROC curve of up to 0.90 and a sensitivity of over 70% at 90% specificity when classifying gene products according to their disease relatedness. This performance is comparable or even superior to related methods in the field, albeit using less and thus more easily accessible information. AVAILABILITY: MedSim is offered as part of our FunSimMat web service (http://www.funsimmat.de).
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