A protein structural study based on the centrality analysis of protein sequence feature networks.
In this paper, we use network approaches to analyze the relations between protein sequence features for the top hierarchical classes of CATH and SCOP. We use fundamental connectivity measures such as correlation (CR), normalized mutual information rate (nMIR), and transfer entropy (TE) to analyze th...
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| Format: | Article |
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Public Library of Science (PLoS)
2021-01-01
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| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0248861&type=printable |
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| author | Xiaogeng Wan Xinying Tan |
| author_facet | Xiaogeng Wan Xinying Tan |
| author_sort | Xiaogeng Wan |
| collection | DOAJ |
| description | In this paper, we use network approaches to analyze the relations between protein sequence features for the top hierarchical classes of CATH and SCOP. We use fundamental connectivity measures such as correlation (CR), normalized mutual information rate (nMIR), and transfer entropy (TE) to analyze the pairwise-relationships between the protein sequence features, and use centrality measures to analyze weighted networks constructed from the relationship matrices. In the centrality analysis, we find both commonalities and differences between the different protein 3D structural classes. Results show that all top hierarchical classes of CATH and SCOP present strong non-deterministic interactions for the composition and arrangement features of Cystine (C), Methionine (M), Tryptophan (W), and also for the arrangement features of Histidine (H). The different protein 3D structural classes present different preferences in terms of their centrality distributions and significant features. |
| format | Article |
| id | doaj-art-614dd598f8fc45dba5b0f0931d74cf21 |
| institution | DOAJ |
| issn | 1932-6203 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-614dd598f8fc45dba5b0f0931d74cf212025-08-20T02:55:31ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01163e024886110.1371/journal.pone.0248861A protein structural study based on the centrality analysis of protein sequence feature networks.Xiaogeng WanXinying TanIn this paper, we use network approaches to analyze the relations between protein sequence features for the top hierarchical classes of CATH and SCOP. We use fundamental connectivity measures such as correlation (CR), normalized mutual information rate (nMIR), and transfer entropy (TE) to analyze the pairwise-relationships between the protein sequence features, and use centrality measures to analyze weighted networks constructed from the relationship matrices. In the centrality analysis, we find both commonalities and differences between the different protein 3D structural classes. Results show that all top hierarchical classes of CATH and SCOP present strong non-deterministic interactions for the composition and arrangement features of Cystine (C), Methionine (M), Tryptophan (W), and also for the arrangement features of Histidine (H). The different protein 3D structural classes present different preferences in terms of their centrality distributions and significant features.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0248861&type=printable |
| spellingShingle | Xiaogeng Wan Xinying Tan A protein structural study based on the centrality analysis of protein sequence feature networks. PLoS ONE |
| title | A protein structural study based on the centrality analysis of protein sequence feature networks. |
| title_full | A protein structural study based on the centrality analysis of protein sequence feature networks. |
| title_fullStr | A protein structural study based on the centrality analysis of protein sequence feature networks. |
| title_full_unstemmed | A protein structural study based on the centrality analysis of protein sequence feature networks. |
| title_short | A protein structural study based on the centrality analysis of protein sequence feature networks. |
| title_sort | protein structural study based on the centrality analysis of protein sequence feature networks |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0248861&type=printable |
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