Noise Management by Molecular Networks Export

@article{citeulike:5804394, abstract = {Author Summary Within cells, fluctuations in molecule numbers are inevitable, since the synthesis and degradation of molecules are not synchronised. Such molecular noise can be transferred to other molecules through regulatory interactions. Noise in molecular networks, and especially in gene expression, has been studied extensively over the past years, both experimentally and through mathematical modelling. In this work, we present a theoretical framework that merges concepts derived from metabolic control analysis (which was originally developed to describe the control in metabolic pathways) with linear noise approximation (a concept from statistical physics). This framework is useful to analyse how noise propagates through molecular networks, how noise can be managed within the networks and how different network designs reduce or enhance noise. The present theory makes use of the natural, hierarchical organization of regulatory networks and makes their noise management more understandable in terms of network structure. Within this paper, we apply the framework to signaling and regulatory cascades, and analyse how feedback and time scale separation influence noise propagation in molecular networks.}, author = {Bruggeman, Frank J. and Bl\"{u}thgen, Nils and Westerhoff, Hans V.}, citeulike-article-id = {5804394}, citeulike-linkout-0 = {http://dx.doi.org/10.1371/journal.pcbi.1000506}, day = {18}, doi = {10.1371/journal.pcbi.1000506}, journal = {PLoS Comput Biol}, keywords = {biochemistry, network, noise, sensitivity, stochastic, theory}, month = {September}, number = {9}, pages = {e1000506+}, posted-at = {2009-09-26 23:14:46}, priority = {2}, publisher = {Public Library of Science}, title = {Noise Management by Molecular Networks}, url = {http://dx.doi.org/10.1371/journal.pcbi.1000506}, volume = {5}, year = {2009} }

TY - JOUR ID - citeulike:5804394 L3 - citeulike-article-id:5804394 N2 - Author Summary Within cells, fluctuations in molecule numbers are inevitable, since the synthesis and degradation of molecules are not synchronised. Such molecular noise can be transferred to other molecules through regulatory interactions. Noise in molecular networks, and especially in gene expression, has been studied extensively over the past years, both experimentally and through mathematical modelling. In this work, we present a theoretical framework that merges concepts derived from metabolic control analysis (which was originally developed to describe the control in metabolic pathways) with linear noise approximation (a concept from statistical physics). This framework is useful to analyse how noise propagates through molecular networks, how noise can be managed within the networks and how different network designs reduce or enhance noise. The present theory makes use of the natural, hierarchical organization of regulatory networks and makes their noise management more understandable in terms of network structure. Within this paper, we apply the framework to signaling and regulatory cascades, and analyse how feedback and time scale separation influence noise propagation in molecular networks. IS - 9 JF - PLoS Comput Biol TI - Noise Management by Molecular Networks PB - Public Library of Science VL - 5 SP - e1000506 KW - biochemistry KW - network KW - noise KW - sensitivity KW - stochastic KW - theory AU - Bruggeman, Frank AU - Blüthgen, Nils AU - Westerhoff, Hans PY - 2009/09/18/ UR - http://dx.doi.org/10.1371/journal.pcbi.1000506 ER -