The relationship between structure and function in locally observed complex networks
Recently, studies looking at the small scale interactions taking place in complex networks have started to unveil the wealth of interactions that occur between groups of nodes. Such findings make the claim for a new systematic methodology to quantify, at node level, how dynamics are influenced (or d...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2013-01-01
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| Series: | New Journal of Physics |
| Online Access: | https://doi.org/10.1088/1367-2630/15/1/013048 |
| _version_ | 1797751700398800896 |
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| author | Cesar H Comin Matheus P Viana Luciano da F Costa |
| author_facet | Cesar H Comin Matheus P Viana Luciano da F Costa |
| author_sort | Cesar H Comin |
| collection | DOAJ |
| description | Recently, studies looking at the small scale interactions taking place in complex networks have started to unveil the wealth of interactions that occur between groups of nodes. Such findings make the claim for a new systematic methodology to quantify, at node level, how dynamics are influenced (or differentiated) by the structure of the underlying system. Here we define a new measure that, based on the dynamical characteristics obtained for a large set of initial conditions, compares the dynamical behavior of the nodes present in the system. Through this measure, we find that the geographic and Barabási–Albert models have a high capacity for generating networks that exhibit groups of nodes with distinct dynamics compared to the rest of the network. The application of our methodology is illustrated with respect to two real systems. In the first we use the neuronal network of the nematode Caenorhabditis elegans to show that the interneurons of the ventral cord of the nematode present a very large dynamical differentiation when compared to the rest of the network. The second application concerns the SIS epidemic model on an airport network, where we quantify how different the distribution of infection times of high and low degree nodes can be, when compared to the expected value for the network. |
| first_indexed | 2024-03-12T16:53:24Z |
| format | Article |
| id | doaj.art-3231b7dd137a4508897354690e00627a |
| institution | Directory Open Access Journal |
| issn | 1367-2630 |
| language | English |
| last_indexed | 2024-03-12T16:53:24Z |
| publishDate | 2013-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | New Journal of Physics |
| spelling | doaj.art-3231b7dd137a4508897354690e00627a2023-08-08T11:04:10ZengIOP PublishingNew Journal of Physics1367-26302013-01-0115101304810.1088/1367-2630/15/1/013048The relationship between structure and function in locally observed complex networksCesar H Comin0Matheus P Viana1Luciano da F Costa2Institute of Physics at São Carlos, University of São Paulo , São Carlos, SP 13560-970, BrazilInstitute of Physics at São Carlos, University of São Paulo , São Carlos, SP 13560-970, BrazilInstitute of Physics at São Carlos, University of São Paulo , São Carlos, SP 13560-970, BrazilRecently, studies looking at the small scale interactions taking place in complex networks have started to unveil the wealth of interactions that occur between groups of nodes. Such findings make the claim for a new systematic methodology to quantify, at node level, how dynamics are influenced (or differentiated) by the structure of the underlying system. Here we define a new measure that, based on the dynamical characteristics obtained for a large set of initial conditions, compares the dynamical behavior of the nodes present in the system. Through this measure, we find that the geographic and Barabási–Albert models have a high capacity for generating networks that exhibit groups of nodes with distinct dynamics compared to the rest of the network. The application of our methodology is illustrated with respect to two real systems. In the first we use the neuronal network of the nematode Caenorhabditis elegans to show that the interneurons of the ventral cord of the nematode present a very large dynamical differentiation when compared to the rest of the network. The second application concerns the SIS epidemic model on an airport network, where we quantify how different the distribution of infection times of high and low degree nodes can be, when compared to the expected value for the network.https://doi.org/10.1088/1367-2630/15/1/013048 |
| spellingShingle | Cesar H Comin Matheus P Viana Luciano da F Costa The relationship between structure and function in locally observed complex networks New Journal of Physics |
| title | The relationship between structure and function in locally observed complex networks |
| title_full | The relationship between structure and function in locally observed complex networks |
| title_fullStr | The relationship between structure and function in locally observed complex networks |
| title_full_unstemmed | The relationship between structure and function in locally observed complex networks |
| title_short | The relationship between structure and function in locally observed complex networks |
| title_sort | relationship between structure and function in locally observed complex networks |
| url | https://doi.org/10.1088/1367-2630/15/1/013048 |
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