000017211 001__ 17211
000017211 005__ 20190219123639.0
000017211 037__ $$aTESIS-2014-108
000017211 041__ $$aspa
000017211 080__ $$a53:579
000017211 1001_ $$aSanz Remón, Joaquín
000017211 24500 $$aTackling complexity in biological systems$$bMulti-scale approaches to tuberculosis infection
000017211 260__ $$aZaragoza$$bUniversidad de Zaragoza, Prensas de la Universidad$$c2014
000017211 300__ $$a406
000017211 4900_ $$aTesis de la Universidad de Zaragoza$$v2014-105$$x2254-7606
000017211 500__ $$aPresentado:  22 10 2014
000017211 502__ $$aTesis-Univ. Zaragoza, Física Teórica, 2014$$bZaragoza, Universidad de Zaragoza$$c2014
000017211 506__ $$aby-nc-nd$$bCreative Commons$$c3.0$$uhttps://creativecommons.org/licenses/by-nc-nd/3.0/
000017211 520__ $$aTuberculosis is an ancient disease responsible for more than a million deaths per year worldwide, whose complex infection cycle involves dynamical processes that take place at different spatial and temporal scales, from single pathogenic cells to entire hosts' populations. In this thesis we study TB disease at different levels of description from the perspective of complex systems sciences.  On the one hand, we use complex networks theory for the analysis of cell interactomes of the causative agent of the disease: the bacillus Mycobacterium tuberculosis. Here, we analyze the gene regulatory network of the bacterium, as well as its network of protein interactions and the way in which it is transformed as a consequence of gene expression adaptation to disparate environments. On the other hand, at the level of human societies, we develop new models for the description of TB spreading on complex populations. First, we develop mathematical models aimed at addressing, from a conceptual perspective, the interplay between complexity of hosts' populations and certain dynamical traits characteristic of TB spreading, like long latency periods and syndemic associations with other diseases. On the other hand, we develop a novel data-driven model for TB spreading with the objective of providing faithful impact evaluations for novel TB vaccines of different types.
000017211 6531_ $$amicrobiología
000017211 6531_ $$afísica aplicada
000017211 700__ $$aMoreno Vega, Yamir$$edir.
000017211 7102_ $$aUniversidad de Zaragoza$$bFísica Teórica
000017211 8560_ $$fzaguan@unizar.es
000017211 8564_ $$s31515424$$uhttps://zaguan.unizar.es/record/17211/files/TESIS-2014-108.pdf$$zTexto completo (spa)
000017211 909CO $$ooai:zaguan.unizar.es:17211$$pdriver
000017211 909co $$ptesis
000017211 9102_ $$aFísica aplicada$$bFísica Teórica
000017211 980__ $$aTESIS