Network-based methods for identifying critical pathways of complex diseases: a survey

被引:16
作者
Zhang, Qiaosheng [1 ,2 ]
Li, Jie [1 ]
Xue, Hanqing [1 ]
Kong, Leilei [3 ]
Wang, Yadong [1 ]
机构
[1] Harbin Inst Technol, Sch Comp Sci & Technol, Harbin, Peoples R China
[2] Heilongjiang Bayi Agr Univ, Heilongjiang, Peoples R China
[3] Heilongjiang Inst Technol, Sch Comp Sci & Technol, Heilongjiang, Peoples R China
基金
中国国家自然科学基金;
关键词
GENE-EXPRESSION; TRANSCRIPTIONAL REGULATION; SIGNALING PATHWAYS; CANCER; CLASSIFICATION; DATABASE; ENZYMES; CONTEXT; KEGG; TOOL;
D O I
10.1039/c5mb00815h
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Biological pathways play important roles in the development of complex diseases, such as cancers, which are multifactorial complex diseases that are generally caused by mutation of multiple genes or dysregulation of pathways. It has become one of the most important issues to analyze pathways through combining multiple types of high-throughput data, such as genomics and proteomics, to understand the mechanisms of complex diseases. Currently, several network-based pathway analysis methods have been proposed. In this overview, we review seven major network-based pathway analysis methods and enumerate their benefits and limitations from an algorithmic perspective to provide a reference for the next generation of pathway analysis methods. Finally, we discuss the challenges that the next generation of methods faces.
引用
收藏
页码:1082 / 1089
页数:8
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