Journal
BMC BIOINFORMATICS
Volume 19, Issue -, Pages -Publisher
BIOMED CENTRAL LTD
DOI: 10.1186/s12859-018-2102-9
Keywords
Phenotype relationships; Interactome; Human phenotype ontology
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Funding
- National Natural Science Foundation of China [61702421, 61602386, 61332014]
- Natural Science Basic Research Plan in Shaanxi Province of China [2017JQ6047]
- China Postdoctoral Science Foundation [2017M610651]
- Fundamental Research Funds for the Central Universities [3102016QD003]
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Background: Recently, measuring phenotype similarity began to play an important role in disease diagnosis. Researchers have begun to pay attention to develop phenotype similarity measurement. However, existing methods ignore the interactions between phenotype-associated proteins, which may lead to inaccurate phenotype similarity. Results: We proposed a network-based method PhenoNet to calculate the similarity between phenotypes. We localized phenotypes in the network and calculated the similarity between phenotype-associated modules by modeling both the inter- and intra-similarity. Conclusions: PhenoNet was evaluated on two independent evaluation datasets: gene ontology and gene expression data. The result shows that PhenoNet performs better than the state-of-art methods on all evaluation tests.
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