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Bioinformatic analysis of the molecular mechanism underlying bronchial pulmonary dysplasia using a text mining approach
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-re...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6946243/ https://www.ncbi.nlm.nih.gov/pubmed/31876736 http://dx.doi.org/10.1097/MD.0000000000018493 |
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author | Zhou, Weitao Shao, Fei Li, Jing |
author_facet | Zhou, Weitao Shao, Fei Li, Jing |
author_sort | Zhou, Weitao |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6946243 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-69462432020-01-31 Bioinformatic analysis of the molecular mechanism underlying bronchial pulmonary dysplasia using a text mining approach Zhou, Weitao Shao, Fei Li, Jing Medicine (Baltimore) 6200 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. Wolters Kluwer Health 2019-12-27 /pmc/articles/PMC6946243/ /pubmed/31876736 http://dx.doi.org/10.1097/MD.0000000000018493 Text en Copyright © 2019 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by/4.0 This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0 |
spellingShingle | 6200 Zhou, Weitao Shao, Fei Li, Jing Bioinformatic analysis of the molecular mechanism underlying bronchial pulmonary dysplasia using a text mining approach |
title | Bioinformatic analysis of the molecular mechanism underlying bronchial pulmonary dysplasia using a text mining approach |
title_full | Bioinformatic analysis of the molecular mechanism underlying bronchial pulmonary dysplasia using a text mining approach |
title_fullStr | Bioinformatic analysis of the molecular mechanism underlying bronchial pulmonary dysplasia using a text mining approach |
title_full_unstemmed | Bioinformatic analysis of the molecular mechanism underlying bronchial pulmonary dysplasia using a text mining approach |
title_short | Bioinformatic analysis of the molecular mechanism underlying bronchial pulmonary dysplasia using a text mining approach |
title_sort | bioinformatic analysis of the molecular mechanism underlying bronchial pulmonary dysplasia using a text mining approach |
topic | 6200 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6946243/ https://www.ncbi.nlm.nih.gov/pubmed/31876736 http://dx.doi.org/10.1097/MD.0000000000018493 |
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