Topological properties of robust biological and computational networks

Navlakha, S., He, X., Faloutsos, C., Bar-Joseph, Z. (July 2014) Topological properties of robust biological and computational networks. J R Soc Interface, 11 (96). p. 20140283. ISSN 1742-5662

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.

Item Type: Paper
Subjects: bioinformatics > computational biology > algorithms
bioinformatics > computational biology
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > genes, structure and function > gene network
CSHL Authors:
Communities: CSHL labs > Navlakha lab
Depositing User: Matthew Dunn
Date: 6 July 2014
Date Deposited: 06 Nov 2019 20:54
Last Modified: 06 Nov 2019 20:54
PMCID: PMC4032542
Related URLs:
URI: https://repository.cshl.edu/id/eprint/38692

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