Complex brain networks are mainly estimated from empirical measurements. As a result, filtering procedures are typically adopted to prune the weakest connections. The structural properties of the thresholded networks depend on the number of remaining links and how to objectively fix such threshold is still an open issue. We propose a possible criterion to filter connectivity based on the optimization of fundamental properties in complex systems, such as efficiency and economy, and we show that a general law can be derived. Given its generality, ECO can advance the ability to analyze biological networks inferred from experimentally obtained data. De Vico Fallani et al.
Image Credit: Fabrizio De Vico Fallani
Editorials
Computing the Dynamic Supramolecular Structural Proteome
PLOS Computational Biology: published January 19, 2017 | https://doi.org/10.1371/journal.pcbi.1005290
Ten Simple Rules to Enable Multi-site Collaborations through Data Sharing
PLOS Computational Biology: published January 19, 2017 | https://doi.org/10.1371/journal.pcbi.1005278
Ten Simple Rules for Developing Usable Software in Computational Biology
PLOS Computational Biology: published January 5, 2017 | https://doi.org/10.1371/journal.pcbi.1005265
Perspective
Efficient Switches in Biology and Computer Science
PLOS Computational Biology: published January 5, 2017 | https://doi.org/10.1371/journal.pcbi.1005100
Review
Pain: A Statistical Account
PLOS Computational Biology: published January 12, 2017 | https://doi.org/10.1371/journal.pcbi.1005142
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