%0 Journal Article %1 citeulike:1292404 %A Almaas, E. %C Microbial Systems Biology, Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, 7000 East Avenue, PO Box 808, L-452, Livermore, CA 94550, USA. %D 2007 %J J Exp Biol %K network, topology %N Pt 9 %P 1548--1558 %R 10.1242/jeb.003731 %T Biological impacts and context of network theory. %U http://dx.doi.org/10.1242/jeb.003731 %V 210 %X Many complex systems can be represented and analyzed as networks, and examples that have benefited from this approach span the natural sciences. For instance, we now know that systems as disparate as the World Wide Web, the Internet, scientific collaborations, food webs, protein interactions and metabolism all have common features in their organization, the most salient of which are their scale-free connectivity distributions and their small-world behavior. The recent availability of large-scale datasets that span the proteome or metabolome of an organism have made it possible to elucidate some of the organizational principles and rules that govern their function, robustness and evolution. We expect that combining the currently separate layers of information from gene regulatory networks, signal transduction networks, protein interaction networks and metabolic networks will dramatically enhance our understanding of cellular function and dynamics.

@article{citeulike:1292404, abstract = {Many complex systems can be represented and analyzed as networks, and examples that have benefited from this approach span the natural sciences. For instance, we now know that systems as disparate as the World Wide Web, the Internet, scientific collaborations, food webs, protein interactions and metabolism all have common features in their organization, the most salient of which are their scale-free connectivity distributions and their small-world behavior. The recent availability of large-scale datasets that span the proteome or metabolome of an organism have made it possible to elucidate some of the organizational principles and rules that govern their function, robustness and evolution. We expect that combining the currently separate layers of information from gene regulatory networks, signal transduction networks, protein interaction networks and metabolic networks will dramatically enhance our understanding of cellular function and dynamics.}, added-at = {2009-05-19T18:00:18.000+0200}, address = {Microbial Systems Biology, Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, 7000 East Avenue, PO Box 808, L-452, Livermore, CA 94550, USA.}, author = {Almaas, E.}, biburl = {https://www.bibsonomy.org/bibtex/2447e75ecbe61884212465fc554716100/earthfare}, citeulike-article-id = {1292404}, description = {CiteULike: Everyone's library}, doi = {10.1242/jeb.003731}, interhash = {f12a3565f08d4285d94b7a178a2c7197}, intrahash = {447e75ecbe61884212465fc554716100}, issn = {0022-0949}, journal = {J Exp Biol}, keywords = {network, topology}, month = May, number = {Pt 9}, pages = {1548--1558}, posted-at = {2009-05-19 15:40:37}, priority = {2}, timestamp = {2009-05-19T18:03:27.000+0200}, title = {Biological impacts and context of network theory.}, url = {http://dx.doi.org/10.1242/jeb.003731}, volume = 210, year = 2007 }