Systems biology beyond degree, hubs and scale-free networks: the case for multiple metrics in complex networks
arXiv:1205.2318 · doi:10.1007/s11693-012-9094-y
Abstract
Modeling and topological analysis of networks in biological and other complex systems, must venture beyond the limited consideration of very few network metrics like degree, betweenness or assortativity. A proper identification of informative and redundant entities from many different metrics, using recently demonstrated techniques, is essential. A holistic comparison of networks and growth models is best achieved only with the use of such methods.
arXiv commentTo appear in Systems and Synthetic Biology (Springer)
References in corpus (10)
- Statistical mechanics of complex networks
- Power-law distributions in empirical data
- Error and attack tolerance of complex networks
- Lethality and centrality in protein networks
- Assortative mixing in networks
- The worldwide air transportation network: Anomalous centrality, community structure, and cities' global roles
- Resilience and rewiring of the passenger airline networks in the United States
- Assortative mixing in Protein Contact Networks and protein folding kinetics
- Strong associations between microbe phenotypes and their network architecture
- Modeling and verifying a broad array of network properties
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