ArticlePloS one2013
Inference of gene-phenotype associations via protein-protein interaction and orthology.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- SSLpheno: a self-supervised learning approach for gene-phenotype association prediction using protein-protein interactions and gene ontology data.Bioinformatics (Oxford, England) · 2023Article
- Computational Methods for Prediction of Human Protein-Phenotype Associations: A Review.Phenomics (Cham, Switzerland) · 2021Review
- Integration of anatomy ontology data with protein-protein interaction networks improves the candidate gene prediction accuracy for anatomical entities.BMC bioinformatics · 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
- Prediction of Human Phenotype Ontology terms by means of hierarchical ensemble methods.BMC bioinformatics · 2017Article
- PHENOstruct: Prediction of human phenotype ontology terms using heterogeneous data sources.F1000Research · 2015Article
Corrections and comments
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Authors and funding
7 authors.
Funding
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Abstract
One of the fundamental goals of genetics is to understand gene functions and their associated phenotypes. To achieve this goal, in this study we developed a computational algorithm that uses orthology and protein-protein interaction information to infer gene-phenotype associations for multiple species. Furthermore, we developed a web server that provides genome-wide phenotype inference for six species: fly, human, mouse, worm, yeast, and zebrafish. We evaluated our inference method by comparing the inferred results with known gene-phenotype associations. The high Area Under the Curve values suggest a significant performance of our method. By applying our method to two human representative diseases, Type 2 Diabetes and Breast Cancer, we demonstrated that our method is able to identify related Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The web server can be used to infer functions and putative phenotypes of a gene along with the candidate genes of a phenotype, and thus aids in disease candidate gene discovery. Our web server is available at http://jjwanglab.org/PhenoPPIOrth.
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Registered trials
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