Biological impacts and context of network theory
- 1 May 2007
- journal article
- review article
- Published by The Company of Biologists in Journal of Experimental Biology
- Vol. 210 (9), 1548-1558
- https://doi.org/10.1242/jeb.003731
Abstract
SUMMARY 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.Keywords
This publication has 63 references indexed in Scilit:
- Evolutionary and Physiological Importance of Hub ProteinsPLoS Computational Biology, 2006
- The Activity Reaction Core and Plasticity of Metabolic NetworksPLoS Computational Biology, 2005
- Large-scale 13C-flux analysis reveals mechanistic principles of metabolic network robustness to null mutations in yeastGenome Biology, 2005
- The architecture of complex weighted networksProceedings of the National Academy of Sciences of the United States of America, 2004
- Global organization of metabolic fluxes in the bacterium Escherichia coliNature, 2004
- Spatial structure of the internet trafficPhysica A: Statistical Mechanics and its Applications, 2003
- Statistical mechanics of complex networksReviews of Modern Physics, 2002
- Error and attack tolerance of complex networksNature, 2000
- Emergence of Scaling in Random NetworksScience, 1999
- More Is DifferentScience, 1972