Development of a network model and investigation of hub proteins for asthma exacerbation
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 conduct...
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| Format: | Article |
| Language: | English |
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International Academy of Ecology and Environmental Sciences
2018-09-01
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| Series: | Network Biology |
| Subjects: | |
| Online Access: | http://www.iaees.org/publications/journals/nb/articles/2018-8(3)/network-model-and-hub-proteins-for-asthma-exacerbation.pdf |
| _version_ | 1811297313540276224 |
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| author | Nazmir-Nur Showva Saleh Ahmed, et al. |
| author_facet | Nazmir-Nur Showva Saleh Ahmed, et al. |
| author_sort | Nazmir-Nur Showva |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T06:02:24Z |
| format | Article |
| id | doaj.art-70025b7f6d934c7cade7692c0264c11b |
| institution | Directory Open Access Journal |
| issn | 2220-8879 2220-8879 |
| language | English |
| last_indexed | 2024-04-13T06:02:24Z |
| publishDate | 2018-09-01 |
| publisher | International Academy of Ecology and Environmental Sciences |
| record_format | Article |
| series | Network Biology |
| spelling | doaj.art-70025b7f6d934c7cade7692c0264c11b2022-12-22T02:59:24ZengInternational Academy of Ecology and Environmental SciencesNetwork Biology2220-88792220-88792018-09-018398112Development of a network model and investigation of hub proteins for asthma exacerbationNazmir-Nur Showva0Saleh Ahmed, et al. 1Department of Biotechnology and Genetic Engineering, Jahangirnagar University, Dhaka-1342, BangladeshDepartment of Biotechnology and Genetic Engineering, Jahangirnagar University, Dhaka-1342, BangladeshAsthma 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.http://www.iaees.org/publications/journals/nb/articles/2018-8(3)/network-model-and-hub-proteins-for-asthma-exacerbation.pdfasthmaprotein interaction networkmolecular complex |
| spellingShingle | Nazmir-Nur Showva Saleh Ahmed, et al. Development of a network model and investigation of hub proteins for asthma exacerbation Network Biology asthma protein interaction network molecular complex |
| title | Development of a network model and investigation of hub proteins for asthma exacerbation |
| title_full | Development of a network model and investigation of hub proteins for asthma exacerbation |
| title_fullStr | Development of a network model and investigation of hub proteins for asthma exacerbation |
| title_full_unstemmed | Development of a network model and investigation of hub proteins for asthma exacerbation |
| title_short | Development of a network model and investigation of hub proteins for asthma exacerbation |
| title_sort | development of a network model and investigation of hub proteins for asthma exacerbation |
| topic | asthma protein interaction network molecular complex |
| url | http://www.iaees.org/publications/journals/nb/articles/2018-8(3)/network-model-and-hub-proteins-for-asthma-exacerbation.pdf |
| work_keys_str_mv | AT nazmirnurshowva developmentofanetworkmodelandinvestigationofhubproteinsforasthmaexacerbation AT salehahmedetal developmentofanetworkmodelandinvestigationofhubproteinsforasthmaexacerbation |