Topological properties of robust biological and computational networks

Abstract

Network robustness is an important principle in biology and engineering. Previous studies of global networks have identified both redundancy and sparseness as topological properties used by robust networks. By focusing on molecular subnetworks, or modules, we show that module topology is tightly linked to the level of environmental variability (noise) the module expects to encounter. Modules internal to the cell that are less exposed to environmental noise are more connected and less robust than external modules. A similar design principle is used by several other biological networks. We propose a simple change to the evolutionary gene duplication model which gives rise to the rich range of module topologies observed within real networks. We apply these observations to evaluate and design communication networks that are specifically optimized for noisy or malicious environments. Combined, joint analysis of biological and computational networks leads to novel algorithms and insights benefiting both fields.

Identification of genes and regulators that are shared across T cell associated diseases

“…On the other hand cell wall organization, endosomal transport are examples of external cell processes less connected and not enriched for essential genes [117]. Even though this study is focused on Saccharomyces cerevisiae authors note similar results for other organisms including bacteria and roundworm and even identified similarities to the computational systems security [117]. Therefore, those findings might be generally applicable.…”

“…Indeed sparser net-works are shown to be more robust [118]. Interestingly in [117] it is shown that modules exposed to greater environmental variation are generally more robust and contain less interactions [117]. On the other hand more essential modules (i.e.…”

“…On the other hand more essential modules (i.e. modules enriched for essential genes 3 ) are located central to the cell and are more densely connected [117]. Examples of internal processes include: transcription initiation, ribosomal subunit, mRNA processing modules.…”

“…In general high connectivity is often linked to redundancy compensating loss-of-function mutations [117]. However same property might lead to cascading effect of local failures [117].…”

“…Modules in general are associated with robustness of biological systems [28,117]. In general high connectivity is often linked to redundancy compensating loss-of-function mutations [117].…”