HIGHLIGHTS
Adaptive metabolic pattern biomarker for disease monitoring and staging of lung cancer with liquid biopsy
npj Precision Oncology - Aug. 8, 2018
In this manuscript, we demonstrate the applicability of a metabolic liquid biopsy for the monitoring and staging of patients with lung cancer. This method provides an unbiased detection strategy to establish a more precise correlation between CTC quantification and the actual burden of disease, therefore improving the accuracy of staging...
Regulation of cell cycle progression by cell–cell and cell–matrix forces
Nat. Cell Biol. - May 25, 2018
It has long been proposed that the cell cycle is regulated by physical forces at the cell–cell and cell–extracellular matrix (ECM) interfaces. However, the evolution of these forces during the cycle has never been measured in a tissue, and whether this evolution affects cell cycle progression is unknown. Here, we...
The importance of being modular
In the 1970s, ecologists began to speculate that modular systems—which are organized into blocks or modules—can better contain perturbations and are therefore more resilient against external damage (1). This simple concept can be applied to any networked system, be it an ecosystem, cellular metabolism, traffic flows, human disease contagion, a...
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.