Comment on "control profiles of complex networks"

Colin Campbell; Katrioma Shea; Réka Albert

doi:10.1126/science.1256492

Comment on "control profiles of complex networks"

Colin Campbell, Katrioma Shea, Réka Albert

Research output: Contribution to journal › Review article › peer-review

10 Scopus citations

Abstract

Ruths and Ruths (Reports, 21 March 2014, p. 1373) find that existing synthetic random network models fail to generate control profiles that match those found in real network models. Here, we show that a straightforward extension to the Barabási-Albert model allows the control profile to be "tuned" across the control profile space, permitting more meaningful control profile analyses of real networks.

Original language	English (US)
Pages (from-to)	561c
Journal	Science
Volume	346
Issue number	6209
DOIs	https://doi.org/10.1126/science.1256492
State	Published - Oct 31 2014

All Science Journal Classification (ASJC) codes

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10.1126/science.1256492

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title = "Comment on {"}control profiles of complex networks{"}",

abstract = "Ruths and Ruths (Reports, 21 March 2014, p. 1373) find that existing synthetic random network models fail to generate control profiles that match those found in real network models. Here, we show that a straightforward extension to the Barab{\'a}si-Albert model allows the control profile to be {"}tuned{"} across the control profile space, permitting more meaningful control profile analyses of real networks.",

author = "Colin Campbell and Katrioma Shea and R{\'e}ka Albert",

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AU - Albert, Réka

PY - 2014/10/31

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N2 - Ruths and Ruths (Reports, 21 March 2014, p. 1373) find that existing synthetic random network models fail to generate control profiles that match those found in real network models. Here, we show that a straightforward extension to the Barabási-Albert model allows the control profile to be "tuned" across the control profile space, permitting more meaningful control profile analyses of real networks.

AB - Ruths and Ruths (Reports, 21 March 2014, p. 1373) find that existing synthetic random network models fail to generate control profiles that match those found in real network models. Here, we show that a straightforward extension to the Barabási-Albert model allows the control profile to be "tuned" across the control profile space, permitting more meaningful control profile analyses of real networks.

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JF - Science

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Comment on "control profiles of complex networks"

Abstract

All Science Journal Classification (ASJC) codes

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