Research

Signaling networks control cellular function, cellular communication and cellular responses, and they do so in an environment subjected to fluctuations. This leads to some broad questions that we try to address in the lab at different levels: How can biological networks integrate and process information from different signals? How can they operate robustly in the presence of noise and undesirable fluctuations? What are the mechanisms underlying adaptation to environmental context? What is the relation between structure and function of simple biological networks?

The advances in experimental techniques and the availability of vasts amounts of data is complementing the traditional molecular approach to research in Biology with a "systems" and quantitative perspective, in which one tries to understand the functioning of a whole decomposing it into simpler "modules" (network motifs), using an approcah that is similar to the engineering and design of complex mechanical and electrical devices. 

We use a combination of mathematical models, numerical simulation and theoretical techniques to investigate some of the above issues, cimbining tools and techiques from non-linear dynamics, together with the theory of stochastic processes, statistical physics, and information and control theory. Apart from doing our own experimetal work, we also work in collaboration with experimental groups where theoretical models can be supported by quantitative data.

The cellular machinery is governed by interacting proteins, genes and metabolites that form complex and highly interconnected networks of interactions. This way, extracellular stimuli triggers pathways of biological events that regulate gene expression, protein activity, and ultimately, cell response. 

The transforming growth factor (TGF-ß) pathway is one of the most conserved and prolific of these signaling cascades, involved in a wide variety of both adult and embryonic processes. We use in vivo experiments and theoretical approaches to understand how the wiring of the pathways determines the role of the proteins that regulate neurogenesis. Therefore, to understand the regulation of neuronal formation it is not sufficient to understand the function of each of the proteins in the pathway. 

A deep understanding of the consequences of the nonlinear wiring of the pathway is required to understand stem cell fate decision and embryogenesis.

Small molecule inhibitors display significant potential as treatment for diseases and cancer progression involving deregulated signal transduction pathways. These inhibitors are developed based on their target specificity and binding affinity, but the fatc that targets are oftene embedded in regulatory positive and negative feedback loops can induce complex dose-responses, desensitization to periodic treatments, or modulation of the drug effect in combinatorial treatments. Our experiments show that the effect of inhibitors strongly depends on the particularities of the architecture of the targeted pathway, which must then be taken into account when designing treatments to inhibit pathogen nonlinear pathways. 

We also focus of the regulation of cell-surface receptors and the interaction with their corresponding ligands, mainly due to their pharmacological importance as selective targets for chemotherapeutic agents. At present, receptors-based drugs represent more than 60% of medicines in the market, designed to treat several diseases like autoimmune illnesses, infectious diseases or even cancer. 

We use a combination of experiments and mathematical modeling to unveil the consequences of the complex binding process and its relevance in the regulation of the signaling, and to stduy how the nonlinear characteristics of the interaction between downstream  proteins ultimately dictates the dynamics and response to drug treatment.