Identifying networks with common organizational principles
Many complex systems can be represented as networks, and the problem of network comparison is becoming increasingly relevant. There are many techniques for network comparison, from simply comparing network summary statistics to sophisticated but computationally costly alignment-based approaches. Yet...
| Main Authors: | , , , , |
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| Format: | Journal article |
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Oxford University Press
2018
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| _version_ | 1797091489481752576 |
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| author | Wegner, AE Ospina-Forero, L Gaunt, RE Deane, C Reinert, GD |
| author_facet | Wegner, AE Ospina-Forero, L Gaunt, RE Deane, C Reinert, GD |
| author_sort | Wegner, AE |
| collection | OXFORD |
| description | Many complex systems can be represented as networks, and the problem of network comparison is becoming increasingly relevant. There are many techniques for network comparison, from simply comparing network summary statistics to sophisticated but computationally costly alignment-based approaches. Yet it remains challenging to accurately cluster networks that are of a different size and density, but hypothesized to be structurally similar. In this paper, we address this problem by introducing a new network comparison methodology that is aimed at identifying common organizational principles in networks. The methodology is simple, intuitive and applicable in a wide variety of settings ranging from the functional classification of proteins to tracking the evolution of a world trade network. |
| first_indexed | 2024-03-07T03:33:51Z |
| format | Journal article |
| id | oxford-uuid:bba1a645-f121-4cd2-aa30-f77c8c2beceb |
| institution | University of Oxford |
| last_indexed | 2024-03-07T03:33:51Z |
| publishDate | 2018 |
| publisher | Oxford University Press |
| record_format | dspace |
| spelling | oxford-uuid:bba1a645-f121-4cd2-aa30-f77c8c2beceb2022-03-27T05:18:20ZIdentifying networks with common organizational principlesJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:bba1a645-f121-4cd2-aa30-f77c8c2becebSymplectic Elements at OxfordOxford University Press2018Wegner, AEOspina-Forero, LGaunt, REDeane, CReinert, GDMany complex systems can be represented as networks, and the problem of network comparison is becoming increasingly relevant. There are many techniques for network comparison, from simply comparing network summary statistics to sophisticated but computationally costly alignment-based approaches. Yet it remains challenging to accurately cluster networks that are of a different size and density, but hypothesized to be structurally similar. In this paper, we address this problem by introducing a new network comparison methodology that is aimed at identifying common organizational principles in networks. The methodology is simple, intuitive and applicable in a wide variety of settings ranging from the functional classification of proteins to tracking the evolution of a world trade network. |
| spellingShingle | Wegner, AE Ospina-Forero, L Gaunt, RE Deane, C Reinert, GD Identifying networks with common organizational principles |
| title | Identifying networks with common organizational principles |
| title_full | Identifying networks with common organizational principles |
| title_fullStr | Identifying networks with common organizational principles |
| title_full_unstemmed | Identifying networks with common organizational principles |
| title_short | Identifying networks with common organizational principles |
| title_sort | identifying networks with common organizational principles |
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