Research Papers:
Prioritizing chronic obstructive pulmonary disease (COPD) candidate genes in COPD-related networks
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Abstract
Yihua Zhang1,*, Wan Li1,*, Yuyan Feng1,*, Shanshan Guo1, Xilei Zhao1, Yahui Wang1, Yuehan He1, Weiming He2 and Lina Chen1
1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang Province, China
2Institute of Opto-Electronics, Harbin Institute of Technology, Harbin, Heilongjiang Province, China
*These authors contributed equally to this work
Correspondence to:
Lina Chen, email: [email protected]
Weiming He, email: [email protected]
Keywords: chronic obstructive pulmonary disease, gene prioritization, metabolic network, protein-protein interaction network, functional information
Received: September 07, 2017 Accepted: October 04, 2017 Published: October 17, 2017
ABSTRACT
Chronic obstructive pulmonary disease (COPD) is a multi-factor disease, which could be caused by many factors, including disturbances of metabolism and protein-protein interactions (PPIs). In this paper, a weighted COPD-related metabolic network and a weighted COPD-related PPI network were constructed base on COPD disease genes and functional information. Candidate genes in these weighted COPD-related networks were prioritized by making use of a gene prioritization method, respectively. Literature review and functional enrichment analysis of the top 100 genes in these two networks suggested the correlation of COPD and these genes. The performance of our gene prioritization method was superior to that of ToppGene and ToppNet for genes from the COPD-related metabolic network or the COPD-related PPI network after assessing using leave-one-out cross-validation, literature validation and functional enrichment analysis. The top-ranked genes prioritized from COPD-related metabolic and PPI networks could promote the better understanding about the molecular mechanism of this disease from different perspectives. The top 100 genes in COPD-related metabolic network or COPD-related PPI network might be potential markers for the diagnosis and treatment of COPD.
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