Open AccessIdentify asthma genes across three phases based on protein–protein interaction network
Author(s) -
Yang Fengyong,
Yu Xianling,
Wang Liping,
Liu Lili,
Xu Xiaorong,
Zheng Xingfeng,
Wei Guangchen
Publication year - 2015
Publication title -
iet systems biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.367
H-Index - 50
eISSN - 1751-8857
pISSN - 1751-8849
DOI - 10.1049/iet-syb.2015.0001
Subject(s) - asthma , computational biology , interaction network , gene , disease , protein–protein interaction , biology , construct (python library) , genetics , bioinformatics , medicine , computer science , immunology , pathology , programming language
Asthma is a common inflammatory disease that is generally caused by genetic mutations or environmental factors. Recently, the emerging of omics data provides an alternative way to understand asthma. In this study, the authors present a new framework to detect asthma disease genes based on protein–protein interaction network (PPIN) and gene expression. Specifically, they construct PPINs for different stages of asthma, and detect those interactions occurred in the specific stages. By investigating the proteins in these stage‐specific interactions, they find they are more likely related to asthma, and the functional enrichment analysis indicate that the pathways enriched in the differential interactions are related to the progress of asthma. Moreover, some proteins in the differential interactions have been previously reported to be related to asthma in the literature, implying the usefulness of the proposed approach.