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Albert-László Barabási
Researcher at Northeastern University
Publications - 463
Citations - 217721
Albert-László Barabási is an academic researcher from Northeastern University. The author has contributed to research in topics: Complex network & Network science. The author has an hindex of 152, co-authored 438 publications receiving 200119 citations. Previous affiliations of Albert-László Barabási include Budapest University of Technology and Economics & Lawrence Livermore National Laboratory.
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Effect of surface roughness on the secondary ion yield in ion sputtering
TL;DR: In this article, the secondary ion yield in terms of parameters characterizing the sputtering process and the interface roughness is calculated analytically in order to calculate the secondary particle density.
Journal ArticleDOI
Liu et al . reply
Yang-Yu Liu,Yang-Yu Liu,Jean-Jacques E. Slotine,Albert-László Barabási,Albert-László Barabási,Albert-László Barabási +5 more
TL;DR: Muller and Schuppert as discussed by the authors showed that roughly 80% of the nodes must be controlled to gain full control over gene regulatory networks, but their result hides subtleties that reveal as much about controllability as about the limits of our current understanding of biological networks.
Posted Content
The Network Behind the Cosmic Web
Bruno Coelho Coutinho,Albert-László Barabási,Sungryong Hong,Kim Albrecht,Arjun Dey,Paul Torrey,Mark Vogelsberger,Lars Hernquist +7 more
TL;DR: In this paper, the authors explore seven network construction algorithms that use various galaxy properties, from their location, to their size and relative velocity, to assign a network to galaxy distributions provided by both simulations and observations.
Posted Content
Fundamental limitations of network reconstruction
TL;DR: It is found that reconstructing any property of the interaction Matrix is generically as difficult as reconstructing the interaction matrix itself, requiring equally informative temporal data.
Journal ArticleDOI
Recovery coupling in multilayer networks
TL;DR: In this paper , the authors explore recovery coupling, capturing the dependence of the recovery of one system on the instantaneous functional state of another system, and find evidence of universal nonlinear behavior in recovery following large perturbations.