Topological Characterization of Complex Systems: Using Persistent Entropy
In this paper, we propose a methodology for deriving a model of a complex system by exploiting the information extracted from topological data analysis. Central to our approach is the S[B] paradigm in which a complex system is represented by a two-level model. One level, the structural S one, is der...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-10-01
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| Series: | Entropy |
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| Online Access: | http://www.mdpi.com/1099-4300/17/10/6872 |
| _version_ | 1798035105639301120 |
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| author | Emanuela Merelli Matteo Rucco Peter Sloot Luca Tesei |
| author_facet | Emanuela Merelli Matteo Rucco Peter Sloot Luca Tesei |
| author_sort | Emanuela Merelli |
| collection | DOAJ |
| description | In this paper, we propose a methodology for deriving a model of a complex system by exploiting the information extracted from topological data analysis. Central to our approach is the S[B] paradigm in which a complex system is represented by a two-level model. One level, the structural S one, is derived using the newly-introduced quantitative concept of persistent entropy, and it is described by a persistent entropy automaton. The other level, the behavioral B one, is characterized by a network of interacting computational agents. The presented methodology is applied to a real case study, the idiotypic network of the mammalian immune system. |
| first_indexed | 2024-04-11T20:53:37Z |
| format | Article |
| id | doaj.art-4cacf6e33d074f36b7a258e9d86330f2 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-04-11T20:53:37Z |
| publishDate | 2015-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-4cacf6e33d074f36b7a258e9d86330f22022-12-22T04:03:46ZengMDPI AGEntropy1099-43002015-10-0117106872689210.3390/e17106872e17106872Topological Characterization of Complex Systems: Using Persistent EntropyEmanuela Merelli0Matteo Rucco1Peter Sloot2Luca Tesei3School of Science and Technology, University of Camerino, Camerino 62032, ItalySchool of Science and Technology, University of Camerino, Camerino 62032, ItalyComputational Science, University of Amsterdam, Amsterdam 1098 XH, The NetherlandsSchool of Science and Technology, University of Camerino, Camerino 62032, ItalyIn this paper, we propose a methodology for deriving a model of a complex system by exploiting the information extracted from topological data analysis. Central to our approach is the S[B] paradigm in which a complex system is represented by a two-level model. One level, the structural S one, is derived using the newly-introduced quantitative concept of persistent entropy, and it is described by a persistent entropy automaton. The other level, the behavioral B one, is characterized by a network of interacting computational agents. The presented methodology is applied to a real case study, the idiotypic network of the mammalian immune system.http://www.mdpi.com/1099-4300/17/10/6872topological data analysispersistent entropy automatonhigher dimensional automataimmune systemidiotypic networkcomputational agents |
| spellingShingle | Emanuela Merelli Matteo Rucco Peter Sloot Luca Tesei Topological Characterization of Complex Systems: Using Persistent Entropy Entropy topological data analysis persistent entropy automaton higher dimensional automata immune system idiotypic network computational agents |
| title | Topological Characterization of Complex Systems: Using Persistent Entropy |
| title_full | Topological Characterization of Complex Systems: Using Persistent Entropy |
| title_fullStr | Topological Characterization of Complex Systems: Using Persistent Entropy |
| title_full_unstemmed | Topological Characterization of Complex Systems: Using Persistent Entropy |
| title_short | Topological Characterization of Complex Systems: Using Persistent Entropy |
| title_sort | topological characterization of complex systems using persistent entropy |
| topic | topological data analysis persistent entropy automaton higher dimensional automata immune system idiotypic network computational agents |
| url | http://www.mdpi.com/1099-4300/17/10/6872 |
| work_keys_str_mv | AT emanuelamerelli topologicalcharacterizationofcomplexsystemsusingpersistententropy AT matteorucco topologicalcharacterizationofcomplexsystemsusingpersistententropy AT petersloot topologicalcharacterizationofcomplexsystemsusingpersistententropy AT lucatesei topologicalcharacterizationofcomplexsystemsusingpersistententropy |