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• W3110792219 abstract "Diabetes-related diseases (DRDs), especially cancers pose a big threat to public health. Although people have explored pathological pathways of a few common DRDs, there is a lack of systematic studies on important biological processes (BPs) connecting diabetes and its related diseases/cancers. We have proposed and compared 10 protein–protein interaction (PPI)-based computational methods to study the connections between diabetes and 254 diseases, among which a method called DIconnectivity_eDMN performs the best in the sense that it infers a disease rank (according to its relation with diabetes) most consistent with that by literature mining. DIconnectivity_eDMN takes diabetes-related genes, other disease-related genes, a PPI network, and genes in BPs as input. It first maps genes in a BP into the PPI network to construct a BP-related subnetwork, which is expanded (in the whole PPI network) by a random walk with restart (RWR) process to generate a so-called expanded modularized network (eMN). Since the numbers of known disease genes are not high, an RWR process is also performed to generate an expanded disease-related gene list. For each eMN and disease, the expanded diabetes-related genes and disease-related genes are mapped onto the eMN. The association between diabetes and the disease is measured by the reachability of their genes on all eMNs, in which the reachability is estimated by a method similar to the Kolmogorov–Smirnov (KS) test. DIconnectivity_eDMN achieves an area under receiver operating characteristic curve (AUC) of 0.71 for predicting both Type 1 DRDs and Type 2 DRDs. In addition, DIconnectivity_eDMN reveals important BPs connecting diabetes and DRDs. For example, “respiratory system development” and “regulation of mRNA metabolic process” are critical in associating Type 1 diabetes (T1D) and many Type 1 DRDs. It is also found that the average proportion of diabetes-related genes interacting with DRDs is higher than that of non-DRDs." @default.
• W3110792219 created "2020-12-21" @default.
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• W3110792219 date "2020-12-14" @default.
• W3110792219 modified "2023-10-16" @default.
• W3110792219 title "Revealing the Interactions Between Diabetes, Diabetes-Related Diseases, and Cancers Based on the Network Connectivity of Their Related Genes" @default.
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• W3110792219 doi "https://doi.org/10.3389/fgene.2020.617136" @default.
• W3110792219 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7767993" @default.
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• W3110792219 hasPublicationYear "2020" @default.
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