HIGHLIGHTS

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Impact of heterogeneity and socioeconomic factors on individual behavior in decentralized sharing ecosystems

Oct. 6, 2014



Tens of millions of individuals around the world use decentralized content distribution systems, a fact of growing social, economic, and technological importance. These sharing systems are poorly understood because, unlike in other technosocial systems, it is difficult to gather large-scale data about user behavior. Here, we investigate user activity patterns...

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Roger Guimerà receives the Young Scientist Award for Socio and Econophysics 2014

by Seeslab, March 31, 2014



Roger Guimerà, ICREA Research Professor at Universitat Rovira i Virgili, in Tarragona, Catalonia, is this year's recipient of the "Young Scientist Award for Socio- and Econophysics" of the German Physical Society (DPG). The Prize, endowed with 5000 euros, recognizes outstanding original contributions by a scientist under 40 that uses physical......

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A network inference method for large-scale unsupervised identification of novel drug-drug interactions

Dec. 5, 2013



Characterizing interactions between drugs is important to avoid potentially harmful combinations, to reduce off-target effects of treatments and to fight antibiotic resistant pathogens, among others. Here we present a network inference algorithm to predict uncharacterized drug-drug interactions. Our algorithm takes, as its only input, sets of previously reported interactions, and...

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OUR RESEARCH

research

Complex Systems

Cells, ecosystems and economies are examples of complex systems. In complex systems, individual components interact with each other, usually in nonlinear ways, giving rise to complex networks of interactions that are neither totally regular nor totally random. Partly because of the interactions themselves and partly because of the interaction's topology, complex systems cannot be properly understood by just analyzing their constituent parts.

research

Data Science

Humans generate information at an unprecedented pace, with some estimates suggesting that, in a year, we now produce on the order of 10^21 bytes of data, millions of times the amount of information in all the books ever written. Processing this "data deluge", as some have called it, requires new tools and new approaches at the interface of statistics, statistical and machine learning, network theory and statistical physics.

research

Multidisciplinarity

Our goal is to push forward the boundaries of science. We are interested in addressing fundamental questions in all areas of science including natural, social and economic sciences. We put a special emphasis in the development of tools that aid scientific discovery through understanding and quantification of a specific phenomenon. To this end we have assembled a multidisciplinary team and have established solid collaborations with experts in biology, social sciences, ecology and economics.