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Network, degeneracy and bow tie. Integrating paradigms and architectures to grasp the complexity of the immune system

Tieri, P; Grignolio, A; Zaikin, A; Mishto, M; Remondini, D; Castellani, GC; Franceschi, C; (2010) Network, degeneracy and bow tie. Integrating paradigms and architectures to grasp the complexity of the immune system. Theoretical Biology and Medical Modelling , 7 (32) 10.1186/1742-4682-7-32. Green open access

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Abstract

Recently, the network paradigm, an application of graph theory to biology, has proven to be a powerful approach to gaining insights into biological complexity, and has catalyzed the advancement of systems biology. In this perspective and focusing on the immune system, we propose here a more comprehensive view to go beyond the concept of network. We start from the concept of degeneracy, one of the most prominent characteristic of biological complexity, defined as the ability of structurally different elements to perform the same function, and we show that degeneracy is highly intertwined with another recently-proposed organizational principle, i.e. 'bow tie architecture'. The simultaneous consideration of concepts such as degeneracy, bow tie architecture and network results in a powerful new interpretative tool that takes into account the constructive role of noise (stochastic fluctuations) and is able to grasp the major characteristics of biological complexity, i.e. the capacity to turn an apparently chaotic and highly dynamic set of signals into functional information.

Type: Article
Title: Network, degeneracy and bow tie. Integrating paradigms and architectures to grasp the complexity of the immune system
Open access status: An open access version is available from UCL Discovery
DOI: 10.1186/1742-4682-7-32
Publisher version: http://dx.doi.org/10.1186/1742-4682-7-32
Language: English
Additional information: © 2010 Tieri et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: T-cell-receptor, Metabolic networks, Stochastic resonance, Cross-reactivity, Recognition, Specificity, Disease, Immunology, Biology, Immunoproteasome
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL EGA Institute for Womens Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL EGA Institute for Womens Health > Womens Cancer
URI: https://discovery.ucl.ac.uk/id/eprint/129872
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