Abstract
Biological network analysis is used to interpret modern high-throughput biomedical data sets in terms of biological functions and pathways. However, the results greatly depend on the topological characteristics of the underlying network, commonly composed of nodes representing genes or proteins that are connected by edges when interacting. In this study, we build biological networks accounting for small molecules, protein isoforms and post-translational modifications. We highlight how these change the global structure of the network and how the connectedness of pathway-based networks is altered. Our findings highlight the importance of carefully crafting the networks for network analysis to better represent the reality of biological systems.
Publisher
Cold Spring Harbor Laboratory