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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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Human disease classification in the postgenomic era: A complex systems approach to human pathobiology
TL;DR: The purpose of this perspective is to provide a logical basis for a new approach to classifying human disease that uses conventional reductionism and incorporates the non‐reductionist approach of systems biomedicine.
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Understanding the spreading patterns of mobile phone viruses.
Pu Wang,Marta C. González,César A. Hidalgo,César A. Hidalgo,César A. Hidalgo,Albert-László Barabási,Albert-László Barabási +6 more
TL;DR: The mobility of mobile phone users is modeled in order to study the fundamental spreading patterns that characterize a mobile virus outbreak and it is found that although Bluetooth viruses can reach all susceptible handsets with time, they spread slowly because of human mobility, offering ample opportunities to deploy antiviral software.
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Life's Complexity Pyramid
TL;DR: Two new studies that investigate both biological networks of intracellular components and nonbiological networks such as the World Wide Web are discussed, explaining that all networks seem to be organized according to the same distinct principles.
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Human symptoms–disease network
TL;DR: It is found that the symptom-based similarity of two diseases correlates strongly with the number of shared genetic associations and the extent to which their associated proteins interact.
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Control Principles of Complex Networks
TL;DR: Recent advances on the controllability and the control of complex networks are reviewed, exploring the intricate interplay between a system's structure, captured by its network topology, and the dynamical laws that govern the interactions between the components.