Bioinformatic analysis of the molecular mechanism underlying bronchial pulmonary dysplasia using a text mining approach.

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ID: 73777
2019
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Abstract
Bronchopulmonary dysplasia (BPD) is a common disease of premature infants with very low birth weight. The mechanism is inconclusive. The aim of this study is to systematically explore BPD-related genes and characterize their functions.Natural language processing analysis was used to identify BPD-related genes. Gene data were extracted from PubMed database. Gene ontology, pathway, and network analysis were carried out, and the result was integrated with corresponding database.In this study, 216 genes were identified as BPD-related genes with P < .05, and 30 pathways were identified as significant. A network of BPD-related genes was also constructed with 17 hub genes identified. In particular, phosphatidyl inositol-3-enzyme-serine/threonine kinase signaling pathway involved the largest number of genes. Insulin was found to be a promising candidate gene related with BPD, suggesting that it may serve as an effective therapeutic target.Our data may help to better understand the molecular mechanisms underlying BPD. However, the mechanisms of BPD are elusive, and further studies are needed.
Reference Key
zhou2019bioinformaticmedicine Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Zhou, Weitao;Shao, Fei;Li, Jing;
Journal Medicine
Year 2019
DOI
10.1097/MD.0000000000018493
URL
Keywords
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