ArticleBMC systems biology2019
Predicting disease-related phenotypes using an integrated phenotype similarity measurement based on HPO.
Article in BMC systems biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Improving automated deep phenotyping through large language models using retrieval-augmented generation.Genome medicine · 2025Article
- Improving patient clustering by incorporating structured variable label relationships in similarity measures.BMC medical research methodology · 2025Article
- Pheno-Ranker: a toolkit for comparison of phenotypic data stored in GA4GH standards and beyond.BMC bioinformatics · 2024Article
- SSLpheno: a self-supervised learning approach for gene-phenotype association prediction using protein-protein interactions and gene ontology data.Bioinformatics (Oxford, England) · 2023Article
- IMPROVE-DD: Integrating multiple phenotype resources optimizes variant evaluation in genetically determined developmental disorders.HGG advances · 2023Article
- A global map of associations between types of protein posttranslational modifications and human genetic diseases.iScience · 2021Article
- Evaluation of standard and semantically-augmented distance metrics for neurology patients.BMC medical informatics and decision making · 2020Article
- A Collection of Benchmark Data Sets for Knowledge Graph-based Similarity in the Biomedical Domain.Database : the journal of biological databases and curation · 2020Article
- Predicting the Disease Genes of Multiple Sclerosis Based on Network Representation Learning.Frontiers in genetics · 2020Article
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3 authors.
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Abstract
backgroundImproving efficiency of disease diagnosis based on phenotype ontology is a critical yet challenging research area. Recently, Human Phenotype Ontology (HPO)-based semantic similarity has been affectively and widely used to identify causative genes and diseases. However, current phenotype similarity measurements just consider the annotations and hierarchy structure of HPO, neglecting the definition description of phenotype terms.
resultsIn this paper, we propose a novel phenotype similarity measurement, termed as DisPheno, which adequately incorporates the definition of phenotype terms in addition to HPO structure and annotations to measure the similarity between phenotype terms. DisPheno also integrates phenotype term associations into phenotype-set similarity measurement using gene and disease annotations of phenotype terms.
conclusionsCompared with five existing state-of-the-art methods, DisPheno shows great performance in HPO-based phenotype semantic similarity measurement and improves the efficiency of disease identification, especially on noisy patients dataset.
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