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Measuring phenotype semantic similarity using Human Phenotype Ontology

机译:使用人类表型本体论衡量表型语义相似性

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It is critical yet remains to be challenging to make right disease diagnosis based on complex clinical characteristic and heterogeneous genetic background. Recently, Human Phenotype Ontology (HPO)-based phenotype similarity has been widely used to aid disease diagnosis. However, the existing measurements are revised based on the Gene Ontology-based term similarity models, which are not optimized for human phenotype ontologies. We propose a new similarity measure called PhenoSim. Our model includes a noise reduction component to model the noisy patient phenotype data, and a path-constrained Information Content-based method for measuring phenotype semantics similarity. Evaluation tests showed that PhenoSim could improve the performance of HPO-based phenotype similarity measurement.
机译:基于复杂的临床特征和异质遗传背景进行正确的疾病诊断仍然至关重要,但仍然具有挑战性。最近,基于人类表型本体论(HPO)的表型相似性已被广泛用于辅助疾病诊断。但是,基于基于基因本体论的术语相似度模型对现有度量进行了修订,而该模型并未针对人类表型本体论进行优化。我们提出了一种新的相似性度量,称为PhenoSim。我们的模型包括一个用于对嘈杂的患者表型数据进行建模的降噪组件,以及一种用于测量表型语义相似性的基于路径约束的基于信息内容的方法。评估测试表明,PhenoSim可以改善基于HPO的表型相似性测量的性能。

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