Predicting disease-related genes using integrated biomedical networks

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• 作者：Jiajie Peng ; Kun Bai ; Xuequn Shang ; Guohua Wang ; Hansheng Xue ; Shuilin Jin…
• 关键词：Disease gene prediction ; Laplacian normalization ; Supervised random walk ; Integrated network
• 刊名：BMC Genomics
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：18
• 期：1-supp
• 全文大小：986KB
• 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：18

文摘

BackgroundIdentifying the genes associated to human diseases is crucial for disease diagnosis and drug design. Computational approaches, esp. the network-based approaches, have been recently developed to identify disease-related genes effectively from the existing biomedical networks. Meanwhile, the advance in biotechnology enables researchers to produce multi-omics data, enriching our understanding on human diseases, and revealing the complex relationships between genes and diseases. However, none of the existing computational approaches is able to integrate the huge amount of omics data into a weighted integrated network and utilize it to enhance disease related gene discovery.