Predicting diabetes mellitus genes via protein-protein interaction and protein subcellular localization information

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• 作者：Xiwei Tang ; Xiaohua Hu ; Xuejun Yang ; Yetian Fan ; Yongfan Li ; Wei Hu…
• 刊名：BMC Genomics
• 出版年：2016
• 出版时间：August 2016
• 年：2016
• 卷：17
• 期：4-supp
• 全文大小：669KB
• 刊物主题：Life Sciences, general; Microarrays; Proteomics; Animal Genetics and Genomics; Microbial Genetics and Genomics; Plant Genetics & Genomics;
• 出版者：BioMed Central
• ISSN：1471-2164
• 卷排序：17

文摘

BackgroundDiabetes mellitus characterized by hyperglycemia as a result of insufficient production of or reduced sensitivity to insulin poses a growing threat to the health of people. It is a heterogeneous disorder with multiple etiologies consisting of type 1 diabetes, type 2 diabetes, gestational diabetes and so on. Diabetes-associated protein/gene prediction is a key step to understand the cellular mechanisms related to diabetes mellitus. Compared with experimental methods, computational predictions of candidate proteins/genes are cheaper and more effortless. Protein-protein interaction (PPI) data produced by the high-throughput technology have been used to prioritize candidate disease genes/proteins. However, the false interactions in the PPI data seriously hurt computational methods performance. In order to address that particular question, new methods are developed to identify candidate disease genes/proteins via integrating biological data from other sources.