title: Network models. 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 Barabási-Albert model allows the control profile to be "tuned" across the control profile space, permitting more meaningful control profile analyses of real networks.
authors.affiliation: Department of Physics, Pennsylvania State University, 122 Davey Laboratory, University Park, PA 16802, USA. Department of Biology, Pennsylvania State University, 208 Mueller Laboratory, University Park, PA 16802, USA. cec220@psu.edu.
authors.forename: Colin
authors.initials: C
authors.lastname: Campbell
authors.affiliation: Department of Biology, Pennsylvania State University, 208 Mueller Laboratory, University Park, PA 16802, USA.
authors.forename: Katriona
authors.initials: K
authors.lastname: Shea
authors.affiliation: Department of Physics, Pennsylvania State University, 122 Davey Laboratory, University Park, PA 16802, USA. Department of Biology, Pennsylvania State University, 208 Mueller Laboratory, University Park, PA 16802, USA.
authors.forename: Réka
authors.initials: R
authors.lastname: Albert
mesh_terms: D006801:Humans; D008962:Models, Theoretical; D013597:Systems Analysis