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- W2950703145 endingPage "e0205936" @default.
- W2950703145 startingPage "e0205936" @default.
- W2950703145 abstract "Many human genetic disorders and diseases are known to be related to each other through frequently observed co-occurrences. Studying the correlations among multiple diseases provides an important avenue to better understand the common genetic background of diseases and to help develop new drugs that can treat multiple diseases. Meanwhile, network science has seen increasing applications on modeling complex biological systems, and can be a powerful tool to elucidate the correlations of multiple human diseases. In this article, known disease-gene associations were represented using a weighted bipartite network. We extracted a weighted human diseases network from such a bipartite network to show the correlations of diseases. Subsequently, we proposed a new centrality measurement for the weighted human disease network (WHDN) in order to quantify the importance of diseases. Using our centrality measurement to quantify the importance of vertices in WHDN, we were able to find a set of most central diseases. By investigating the 30 top diseases and their most correlated neighbors in the network, we identified disease linkages including known disease pairs and novel findings. Our research helps better understand the common genetic origin of human diseases and suggests top diseases that likely induce other related diseases." @default.
- W2950703145 created "2019-06-27" @default.
- W2950703145 creator A5075046931 @default.
- W2950703145 creator A5088631549 @default.
- W2950703145 date "2019-03-22" @default.
- W2950703145 modified "2023-10-16" @default.
- W2950703145 title "Measuring the importance of vertices in the weighted human disease network" @default.
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- W2950703145 doi "https://doi.org/10.1371/journal.pone.0205936" @default.
- W2950703145 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6430629" @default.
- W2950703145 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30901770" @default.
- W2950703145 hasPublicationYear "2019" @default.
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