Data analysis using circular causality in networks
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http://hdl.handle.net/10045/37724
Título: | Data analysis using circular causality in networks |
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Autor/es: | Lloret-Climent, Miguel | Nescolarde-Selva, Josué Antonio |
Grupo/s de investigación o GITE: | Sistémica, Cibernética y Optimización (SCO) |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Matemática Aplicada |
Palabras clave: | Circular causality | Attractor | Chaos theory | Inflammatory diseases | Transcription factors |
Área/s de conocimiento: | Matemática Aplicada |
Fecha de publicación: | mar-2014 |
Editor: | Wiley Periodicals |
Cita bibliográfica: | Complexity. 2014, 19(4): 15-19. doi:10.1002/cplx.21480 |
Resumen: | Complex systems in causal relationships are known to be circular rather than linear; this means that a particular result is not produced by a single cause, but rather that both positive and negative feedback processes are involved. However, although interpreting systemic interrelationships requires a language formed by circles, this has only been developed at the diagram level, and not from an axiomatic point of view. The first difficulty encountered when analysing any complex system is that usually the only data available relate to the various variables, so the first objective was to transform these data into cause-and-effect relationships. Once this initial step was taken, our discrete chaos theory could be applied by finding the causal circles that will form part of the system attractor and allow their behavior to be interpreted. As an application of the technique presented, we analyzed the system associated with the transcription factors of inflammatory diseases. |
URI: | http://hdl.handle.net/10045/37724 |
ISSN: | 1076-2787 (Print) | 1099-0526 (Online) |
DOI: | 10.1002/cplx.21480 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © 2013 Wiley Periodicals, Inc. |
Revisión científica: | si |
Versión del editor: | http://dx.doi.org/10.1002/cplx.21480 |
Aparece en las colecciones: | INV - SYC - Artículos de Revistas |
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2014_Lloret_Nescolarde_Complexity_final.pdf | Versión final (acceso restringido) | 93,51 kB | Adobe PDF | Abrir Solicitar una copia |
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