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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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Uncovering the genetic blueprint of the C. elegans nervous system
István Kovács,Dániel L. Barabási,Albert-László Barabási,Albert-László Barabási,Albert-László Barabási +4 more
TL;DR: A computational framework is introduced to link the adjacency matrix of a connectome to the expression patterns of its neurons, helping to uncover a set of genetic rules that govern the interactions between adjacent neurons.
Journal ArticleDOI
Erratum: Universality in network dynamics
TL;DR: In the version of this article originally published, the expression for Gij on page 673 should have included an absolute value sign and the caption for Fig. 1b1-c4 was missing the final wording as mentioned in this paper.
Journal ArticleDOI
Isotopy and energy of physical networks
Yanchen Liu,Nima Dehmamy,Nima Dehmamy,Albert-László Barabási,Albert-László Barabási,Albert-László Barabási +5 more
TL;DR: In this paper, the authors introduce the concept of network isotopy, representing different network layouts that can be transformed into one another without link crossings, and show that a single quantity, the graph linking number, captures the entangledness of a layout, defining distinct isotopy classes.
Journal ArticleDOI
Anomalous interface roughening in 3D porous media: experiment and model
Sergey V. Buldyrev,Albert-László Barabási,Shlomo Havlin,Shlomo Havlin,János Kertész,H. E. Stanley,H.S. Xenias +6 more
TL;DR: In this article, the authors report the first imbibition experiments in 2 + 1 dimensions using simple materials as the random media and various aqueous suspensions as wetting fluids, and they measure the width w ( l, t ) of the resulting interface and find it to scale with length l as w( l, ∞) ∼ l α with α = 0.50±0.05.
Journal ArticleDOI
Uncovering the genetic blueprint of the C. elegans nervous system.
TL;DR: A computational framework is introduced to link the adjacency matrix of a connectome to the expression patterns of its neurons, helping to uncover a set of genetic rules that govern the interactions between neurons in contact.