Nonlinearity and complex systems
Dynamical systems - Mathematical medicine - Bifurcations - RNA virus - Systems biology - Theoretical ecology - Origins of life - Chaos - Mathematical biology
Everything moves in our world. Mathematics can allow us to understand and sometimes predict these motions (dynamics). For instance, a wolf in the forest will hunt preys to feed himself and the energy gained will be used for reproduction. If the predation is very intensive, prey populations will diminish and once they reach very low numbers, wolves will also decrease, producing a further increase of preys individuals, and so on and so forth. Following these simple (but realistic) rules one can think that the populations of wolves and preys will increase and decrease in time, giving place to some kind of oscillations. Mathematical models describing these interactions indeed produce these oscillations. This is fascinating, isn't it ?
Nonlinear dynamics are ubiquitous in natural and artificial systems. From climate, to lasers, viral dynamics and complex ecosystems. Our Lab is interested in the study of nonlinear systems, focusing on the dynamics and transitions in biological sciences and biomedicine. We use tools from dynamical systems theory and statistical physics to comprehend the mechanisms behind the dynamics and changes of states in nonlinear systems. Specially, we are interested in bifurcation phenomena governing complex biological systems.
Our lab is doing research in many different scientific disciplines under the umbrella of nonlinear dynamics. To achieve our goals, the NoDE Lab is supported by a big network of enthusiastic collaborators specialised in dynamical systems, applied mathematicians, systems and synthetic biologists, as well as field and theoretical ecologists.
“Scientists are perennially aware that it is best not to trust theory until it is confirmed by evidence. It is equally true . . . that it is best not to put too much faith in facts until they have been confirmed by theory.”
Robert MacArthur (Geographical Ecology, 1972)