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Bridging the gap between modules in isolation and as part of networks: A systems framework for elucidating interaction and regulation of signalling modules
Author(s) -
Govind Me,
J. Krishnan
Publication year - 2016
Publication title -
the journal of chemical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.071
H-Index - 357
eISSN - 1089-7690
pISSN - 0021-9606
DOI - 10.1063/1.4953914
Subject(s) - bridging (networking) , bistability , computer science , distributed computing , isolation (microbiology) , signalling , biology , materials science , bioinformatics , computer network , optoelectronics , microbiology and biotechnology
© 2016 Author(s).While signalling and biochemical modules have been the focus of numerous studies, they are typically studied in isolation, with no examination of the effects of the ambient network. In this paper we formulate and develop a systems framework, rooted in dynamical systems, to understand such effects, by studying the interaction of signalling modules. The modules we consider are (i) basic covalent modification, (ii) monostable switches, (iii) bistable switches, (iv) adaptive modules, and (v) oscillatory modules. We systematically examine the interaction of these modules by analyzing (a) sequential interaction without shared components, (b) sequential interaction with shared components, and (c) oblique interactions. Our studies reveal that the behaviour of a module in isolation may be substantially different from that in a network, and explicitly demonstrate how the behaviour of a given module, the characteristics of the ambient network, and the possibility of shared components can result in new effects. Our global approach illuminates different aspects of the structure and functioning of modules, revealing the importance of dynamical characteristics as well as biochemical features; this provides a methodological platform for investigating the complexity of natural modules shaped by evolution, elucidating the effects of ambient networks on a module in multiple cellular contexts, and highlighting the capabilities and constraints for engineering robust synthetic modules. Overall, such a systems framework provides a platform for bridging the gap between non-linear information processing modules, in isolation and as parts of networks, and a basis for understanding new aspects of natural and engineered cellular networks

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