Systems biology beyond degree, hubs and scale-free networks: the case for multiple metrics in complex networks

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.

To appear in Systems and Synthetic Biology (Springer)

References in corpus (4)

• Power-law distributions in empirical data
• 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

Cited by in corpus (3)

• Slow poisoning and destruction of networks: Edge proximity and its implications for biological and infrastructure networks
• Mining Functionally Related Genes with Semi-Supervised Learning
• Investigating cognitive ability using action-based models of structural brain networks