HIGHLIGHTS
Network science article in La Vaguardia
by Seeslab, July 16, 2014
We believe that scientists should strive to reach the broader public, explaining what we do and why it is important. We have recently published an article in the Catalan newspaper La Vanguardia explaining the promise of network research. Here is the Catalan version and here the Spanish version.......
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......
A network inference method for large-scale unsupervised identification of novel drug-drug interactions
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...
OUR 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.
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.
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.