RT Journal Article
SR Electronic
T1 A new computational model captures fundamental architectural features of diverse biological networks
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 046813
DO 10.1101/046813
A1 Bader Al-Anzi
A1 Noah Olsman
A1 Christopher Ormerod
A1 Sherif Gerges
A1 Georgios Piliouras
A1 John Ormerod
A1 Kai Zinn
YR 2016
UL http://biorxiv.org/content/early/2016/04/02/046813.abstract
AB Complex biological systems are often represented by network graphs; however, their structural features are not adequately captured by existing computational graph models, perhaps because the datasets used to assemble them are incomplete and contain elements that lack shared functions. Here, we analyze three large, near-complete networks that produce specific cellular or behavioral outputs: a molecular yeast mitochondrial regulatory protein network, and two anatomical networks of very different scale, the mouse brain mesoscale connectivity network, and the C. elegans neuronal network. Surprisingly, these networks share similar characteristics. All consist of large communities composed of modules with general functions, and topologically distinct subnetworks spanning modular boundaries responsible for their more specific phenotypical outputs. We created a new model, SBM-PS, which generates networks by combining communities, followed by adjustment of connections by a ‘path selection’ mechanism. This model captures fundamental architectural features that are common to the three networks.