A Node Ranking Method Based on Multiple Layers for Dynamic Protein Interaction Networks
Constructing dynamic protein interaction networks (DPIN) is a common way to improve identification accuracy of essential proteins. The existing methods usually aggregate DPIN into a single-layer network where all nodes are sorted by their importance. This treatment makes the dynamic information abou...
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| Format: | Article |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9874843/ |
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| author | Bin Li Li Pan Jing Sun Haoyue Wang Junqiang Jiang Bo Yang Wenbin Li |
| author_facet | Bin Li Li Pan Jing Sun Haoyue Wang Junqiang Jiang Bo Yang Wenbin Li |
| author_sort | Bin Li |
| collection | DOAJ |
| description | Constructing dynamic protein interaction networks (DPIN) is a common way to improve identification accuracy of essential proteins. The existing methods usually aggregate DPIN into a single-layer network where all nodes are sorted by their importance. This treatment makes the dynamic information about proteins in multiple layers lost in the single layer, and thus affects the identification accuracy of essential proteins. This paper proposes a node ranking method based on multiple layers for DPIN to address the problem. First, we calculate the centrality values of all nodes for each time-specific layer, then work out the centrality score of each node by dividing the total of its centrality values across all layers by its layer activity, and finally sort the importance of all nodes by their centrality scores. Different from the methods based on single layer, our method makes full use of centrality values of each protein in time-specific layers, and thus can more effectively utilize the dynamic information of proteins. To evaluate the effectiveness of the node ranking method based on multiple layers, we apply ten network-based centrality methods on multiple layers and compare the results with those on a single layer. Then the predictive performance of the ten centrality methods are validated in terms of sensitivity, specificity, positive predictive value, negative predictive value, F-measure and accuracy. The experimental results for the identification of essential proteins show that the node ranking method based on multiple layers is superior to those based on a single layer and can help to identify essential proteins more accurate. |
| format | Article |
| id | doaj-art-181a1c697ea4477093ba41663bb9f6d5 |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-181a1c697ea4477093ba41663bb9f6d52025-08-20T02:33:48ZengIEEEIEEE Access2169-35362022-01-0110933269333710.1109/ACCESS.2022.32034379874843A Node Ranking Method Based on Multiple Layers for Dynamic Protein Interaction NetworksBin Li0Li Pan1Jing Sun2Haoyue Wang3Junqiang Jiang4https://orcid.org/0000-0002-6934-0113Bo Yang5https://orcid.org/0000-0003-4210-8864Wenbin Li6https://orcid.org/0000-0002-2317-3495Department of Information Science and Engineering, Hunan Institute of Science and Technology, Yueyang, ChinaDepartment of Information Science and Engineering, Hunan Institute of Science and Technology, Yueyang, ChinaDepartment of Information Science and Engineering, Hunan Institute of Science and Technology, Yueyang, ChinaDepartment of Information Science and Engineering, Hunan Institute of Science and Technology, Yueyang, ChinaDepartment of Information Science and Engineering, Hunan Institute of Science and Technology, Yueyang, ChinaDepartment of Information Science and Engineering, Hunan Institute of Science and Technology, Yueyang, ChinaDepartment of Information Science and Engineering, Hunan Institute of Science and Technology, Yueyang, ChinaConstructing dynamic protein interaction networks (DPIN) is a common way to improve identification accuracy of essential proteins. The existing methods usually aggregate DPIN into a single-layer network where all nodes are sorted by their importance. This treatment makes the dynamic information about proteins in multiple layers lost in the single layer, and thus affects the identification accuracy of essential proteins. This paper proposes a node ranking method based on multiple layers for DPIN to address the problem. First, we calculate the centrality values of all nodes for each time-specific layer, then work out the centrality score of each node by dividing the total of its centrality values across all layers by its layer activity, and finally sort the importance of all nodes by their centrality scores. Different from the methods based on single layer, our method makes full use of centrality values of each protein in time-specific layers, and thus can more effectively utilize the dynamic information of proteins. To evaluate the effectiveness of the node ranking method based on multiple layers, we apply ten network-based centrality methods on multiple layers and compare the results with those on a single layer. Then the predictive performance of the ten centrality methods are validated in terms of sensitivity, specificity, positive predictive value, negative predictive value, F-measure and accuracy. The experimental results for the identification of essential proteins show that the node ranking method based on multiple layers is superior to those based on a single layer and can help to identify essential proteins more accurate.https://ieeexplore.ieee.org/document/9874843/Essential proteinsdynamic protein interaction networksmultiple layerscentrality methodsnode ranking |
| spellingShingle | Bin Li Li Pan Jing Sun Haoyue Wang Junqiang Jiang Bo Yang Wenbin Li A Node Ranking Method Based on Multiple Layers for Dynamic Protein Interaction Networks IEEE Access Essential proteins dynamic protein interaction networks multiple layers centrality methods node ranking |
| title | A Node Ranking Method Based on Multiple Layers for Dynamic Protein Interaction Networks |
| title_full | A Node Ranking Method Based on Multiple Layers for Dynamic Protein Interaction Networks |
| title_fullStr | A Node Ranking Method Based on Multiple Layers for Dynamic Protein Interaction Networks |
| title_full_unstemmed | A Node Ranking Method Based on Multiple Layers for Dynamic Protein Interaction Networks |
| title_short | A Node Ranking Method Based on Multiple Layers for Dynamic Protein Interaction Networks |
| title_sort | node ranking method based on multiple layers for dynamic protein interaction networks |
| topic | Essential proteins dynamic protein interaction networks multiple layers centrality methods node ranking |
| url | https://ieeexplore.ieee.org/document/9874843/ |
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