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Prioritizing chronic obstructive pulmonary disease (COPD) candidate genes in COPD-related networks.
Zhang, Yihua; Li, Wan; Feng, Yuyan; Guo, Shanshan; Zhao, Xilei; Wang, Yahui; He, Yuehan; He, Weiming; Chen, Lina.
Affiliation
  • Zhang Y; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang Province, China.
  • Li W; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang Province, China.
  • Feng Y; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang Province, China.
  • Guo S; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang Province, China.
  • Zhao X; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang Province, China.
  • Wang Y; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang Province, China.
  • He Y; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang Province, China.
  • He W; Institute of Opto-Electronics, Harbin Institute of Technology, Harbin, Heilongjiang Province, China.
  • Chen L; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang Province, China.
Oncotarget ; 8(61): 103375-103384, 2017 Nov 28.
Article in En | MEDLINE | ID: mdl-29262568
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Oncotarget Year: 2017 Document type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Oncotarget Year: 2017 Document type: Article Affiliation country: China