Predicting disease-related phenotypes using an integrated phenotype similarity measurement based on HPO

Hansheng Xue, Jiajie Peng, Xuequn Shang

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13 引用 (Scopus)

摘要

Background: Improving 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. Results: In 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. Conclusions: Compared 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.

源语言英语
文章编号34
期刊BMC Systems Biology
13
DOI
出版状态已出版 - 5 4月 2019

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