A natural class of robust networks Export

@article{citeulike:1036517, abstract = {10.1073/pnas.1536783100 As biological studies shift from molecular description to system analysis we need to identify the design principles of large intracellular networks. In particular, without knowing the molecular details, we want to determine how cells reliably perform essential intracellular tasks. Recent analyses of signaling pathways and regulatory transcription networks have revealed a common network architecture, termed scale-free topology. Although the structural properties of such networks have been thoroughly studied, their dynamical properties remain largely unexplored. We present a prototype for the study of dynamical systems to predict the functional robustness of intracellular networks against variations of their internal parameters. We demonstrate that the dynamical robustness of these complex networks is a direct consequence of their scale-free topology. By contrast, networks with homogeneous random topologies require fine-tuning of their internal parameters to sustain stable dynamical activity. Considering the ubiquity of scale-free networks in nature, we hypothesize that this topology is not only the result of aggregation processes such as preferential attachment; it may also be the result of evolutionary selective processes.}, address = {The James Franck Institute, University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637, USA. maximino@control.uchicago.edu}, author = {Aldana, Maximino and Cluzel, Philippe}, citeulike-article-id = {1036517}, citeulike-linkout-0 = {http://dx.doi.org/10.1073/pnas.1536783100}, citeulike-linkout-1 = {http://www.pnas.org/content/100/15/8710.abstract}, citeulike-linkout-2 = {http://www.pnas.org/content/100/15/8710.full.pdf}, citeulike-linkout-3 = {http://www.pnas.org/cgi/content/abstract/100/15/8710}, citeulike-linkout-4 = {http://view.ncbi.nlm.nih.gov/pubmed/12853565}, citeulike-linkout-5 = {http://www.hubmed.org/display.cgi?uids=12853565}, day = {22}, doi = {10.1073/pnas.1536783100}, issn = {0027-8424}, journal = {Proceedings of the National Academy of Sciences of the United States of America}, keywords = {genetic\_regulatory\_networks, network\_theory}, month = {July}, number = {15}, pages = {8710--8714}, posted-at = {2007-01-25 02:40:37}, priority = {4}, title = {A natural class of robust networks}, url = {http://dx.doi.org/10.1073/pnas.1536783100}, volume = {100}, year = {2003} }

TY - JOUR ID - citeulike:1036517 L3 - citeulike-article-id:1036517 N2 - 10.1073/pnas.1536783100 As biological studies shift from molecular description to system analysis we need to identify the design principles of large intracellular networks. In particular, without knowing the molecular details, we want to determine how cells reliably perform essential intracellular tasks. Recent analyses of signaling pathways and regulatory transcription networks have revealed a common network architecture, termed scale-free topology. Although the structural properties of such networks have been thoroughly studied, their dynamical properties remain largely unexplored. We present a prototype for the study of dynamical systems to predict the functional robustness of intracellular networks against variations of their internal parameters. We demonstrate that the dynamical robustness of these complex networks is a direct consequence of their scale-free topology. By contrast, networks with homogeneous random topologies require fine-tuning of their internal parameters to sustain stable dynamical activity. Considering the ubiquity of scale-free networks in nature, we hypothesize that this topology is not only the result of aggregation processes such as preferential attachment; it may also be the result of evolutionary selective processes. IS - 15 JF - Proceedings of the National Academy of Sciences of the United States of America SN - 0027-8424 AD - The James Franck Institute, University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637, USA. maximino@control.uchicago.edu EP - 8714 TI - A natural class of robust networks VL - 100 SP - 8710 KW - genetic_regulatory_networks KW - network_theory AU - Aldana, Maximino AU - Cluzel, Philippe PY - 2003/07/22/ UR - http://dx.doi.org/10.1073/pnas.1536783100 ER -