| Autor: |
Nazmir-Nur Showva, Saleh Ahmed, et al. |
| Jazyk: |
angličtina |
| Rok vydání: |
2018 |
| Předmět: |
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| Zdroj: |
Network Biology, Vol 8, Iss 3, Pp 98-112 (2018) |
| Druh dokumentu: |
article |
| ISSN: |
2220-8879 |
| Popis: |
Asthma is a long-term inflammatory disease known to affect the airways in the lungs with variable and recurring symptoms. A large number of genes, transcription factors and proteins are involved in this process, which makes it polygenic. We investigated the responsible proteins for asthma by conducting in-depth analysis in the database of asthma proteins and subsequently examining their differential role in disease progression following a computational biological approach. Firstly, we constructed a protein-protein interaction network among 1152 proteins, and identified top 20 high degree nodes (known as hubs); considering threshold score of ≥100 by using Cytoscape 3.1.0 software package. Also we identified seven asthma signal transduction pathways from KEGG database and compared them with the pathways derived from NetWalker platform to determine the constituted proteins. Secondly, we conducted MCODE (molecular complex detection) analysis that divided the network into 27 clusters having threshold score of ≥4.0. These individual clusters of constituted proteins were compared with the hubs and the results demonstrated their functional role in asthma. We also identified the proteins involved in the regulatory, reactome and metabolic reaction interaction for asthma exacerbation, classified different lung functional roles of these proteins, and found hyper-geometric pvalue of ≤0.05. Thus, our in-depth analysis suggests some important consequences for interpreting the resulting data significantly and gives more insight about asthma exacerbation. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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