ArticleF1000Research2015
PHENOstruct: Prediction of human phenotype ontology terms using heterogeneous data sources.
Article in F1000Research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Expanding the utility of variant effect predictions with phenotype-specific models.Nature communications · 2025Article
- Article
- Network-Based Methods for Approaching Human Pathologies from a Phenotypic Point of View.Genes · 2022Review
- Ontology-aware deep learning enables ultrafast and interpretable source tracking among sub-million microbial community samples from hundreds of niches.Genome medicine · 2022Article
- Gene prediction of aging-related diseases based on DNN and Mashup.BMC bioinformatics · 2021Article
- Deep semi-supervised learning ensemble framework for classifying co-mentions of human proteins and phenotypes.BMC bioinformatics · 2021Article
- Computational Methods for Prediction of Human Protein-Phenotype Associations: A Review.Phenomics (Cham, Switzerland) · 2021Review
- Semantic similarity and machine learning with ontologies.Briefings in bioinformatics · 2021Review
- Systematic identification of genetic systems associated with phenotypes in patients with rare genomic copy number variations.Human genetics · 2021Article
- DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier.PLoS computational biology · 2020Article
- HPOAnnotator: improving large-scale prediction of HPO annotations by low-rank approximation with HPO semantic similarities and multiple PPI networks.BMC medical genomics · 2019Article
- Ontology-based validation and identification of regulatory phenotypes.Bioinformatics (Oxford, England) · 2018Article
- Measuring phenotype-phenotype similarity through the interactome.BMC bioinformatics · 2018Article
- Article
- Prediction of Human Phenotype Ontology terms by means of hierarchical ensemble methods.BMC bioinformatics · 2017Article
- The Interaction Network Ontology-supported modeling and mining of complex interactions represented with multiple keywords in biomedical literature.BioData mining · 2016Article
- PHENOstruct: Prediction of human phenotype ontology terms using heterogeneous data sources.F1000Research · 2015Article
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4 authors.
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Abstract
The human phenotype ontology (HPO) was recently developed as a standardized vocabulary for describing the phenotype abnormalities associated with human diseases. At present, only a small fraction of human protein coding genes have HPO annotations. But, researchers believe that a large portion of currently unannotated genes are related to disease phenotypes. Therefore, it is important to predict gene-HPO term associations using accurate computational methods. In this work we demonstrate the performance advantage of the structured SVM approach which was shown to be highly effective for Gene Ontology term prediction in comparison to several baseline methods. Furthermore, we highlight a collection of informative data sources suitable for the problem of predicting gene-HPO associations, including large scale literature mining data.
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