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ZENODO
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Data sources: ZENODO
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F1000Research/Network-Randomizer: F1000Reserach/Network-Randomizer

Authors: gabrielet; Ivan Bestvina;

F1000Research/Network-Randomizer: F1000Reserach/Network-Randomizer

Abstract

Network Randomizer is a Cytoscape app for generating random networks, as well as randomizing the existing ones, by using multiple random network models. Further, it can process the statistical information gained from the these networks in order to pinpoint their special, non-random characteristics. It covers many popular random network models: Erdős–Rényi, Watts–Strogatz, Barabási–Albert, Community Affiliation Graph, edge shuffle, degree preserving edge shuffle, but it also features a new model which is based on the node multiplication. The statistical module is based on the two-sample Kolmogorov-Smirnov test. It compares random and real networks finding the differences between them and thus providing insight into non-random processes upon which real networks are built. The app was developed by Gabriele Tosadori and Ivan Bestvina, as a project for the National Resource for Network Biology.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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