I belong to the Complex Systems Lab, at the University Pompeu Fabra, in Barcelona, where I lead the Complex Systems Wet Lab and I teach synthetic biology and biological engineering.
From the perspective of Systems and Synthetic Biology
my research interest is concerned with the principles of
(auto)organisation at molecular and cellular level. With a background
of Biology, my research spans different branches of Molecular Biology, Physics and Computation applied to the study of
complex biological networks and dynamical systems. The emergence of collective behaviours at the cellular
level, multi-cellularity and the study of cancer as a
micro-evolutionary process are some examples of my research interests.
Research topics:
Synthetic Biology:
Synthetic Biology is a emerging discipline devoted to design and construct new biological parts, devices, and systems, and the re-design of existing, natural biological systems for useful purposes. In this approach my interest is to combine mathematical models and experiments using standarized genetic parts from partregistry.org for different purposes.
Design of genetic circuits with biomedical interest using prokaryotic chasis.
Human microbiome constitutes a promising non-invasive way to define strategies for biomedical applications. In our group we are developing strategies to restore metabolic disorders through the use of synthetic biology.
Principles of design of genetic circuitry for biosensors.
Tunning suitable and reliable responses by the correct stimuli is a key issue in any biomedical and biotechnological application. Inspired in biology, natural genetic circuits seem to exhibit their own logic. Taking advantage of dynamical models we examine from a mathematical perspective the circuitry of known biological mechanisms and their properties in order to acquire robust, sensitive and reliable behaviours. Our experience is then translated to the experimental implementation of sinthetic genetic circuits capturing the logic of the desired behaviour.
Principles of organisation for the emergence of synthetic multicelularity.
From the perspective of Synthetic biology, can we define a minimal toolbox for inducing synthetic multicelularity? The view of synthetic biology can contribute as a reverse enginnering aproach to get insight about the requisites for one cell population that, sharing the same genetic information, decides to cooperate in a single body. If we are able to define a minimal logic for encoding cell cooperation, we will be able to design complex behaviours at cell population levels. This idea allows to explore more complex behaviours going further the cellular behaviour such as task distribution and proper cell specialisation according requirements. Inspired and taking advantge of quorum sensing genetics of microorganism, one of our main interests is the development of a genetic toolbox for the emergence of spatial pattern formation through the introduction of a synthetic genetic circuitry in unicellular organisms that do not exhibit this behaviour.
Systems Biology:
Systems biology pursues the study of biological systems, mainly at molecular, celular and organism level. With the idea of studying the system as a whole, Systems Biology provides a knowledge that goes beyong the study of system's components.
Study of very-large (biomolecular) systems by the use of complex network approximation.
In a coarse-grained approach network thinking provides us a map of the interactions of systems made of huge numbers of components. My interest regards with the study of the biomolecular networks related to metabolism and its control through gene regulatory networks, as well as the representation of diseases in a systemis way, as it is the case of the so-called synthetic lethal gene interaction networks. In this context, network thinking provides excellent tools for network characterisation, but also a framework for tackling more ambitious and still open questions. How cellular networks are organised? What are the driving forces which have operated during evolution?
The concept of hierarchy in complex networks
My recent interest in this isssue has allowed me to explore the concept of hierarchy of complex networks going beyond cellular systems. In a more theoretical approach within the field of statitical mechanism and graph theory I have got the opportunity to explore the concept of hierarchy. The result of this work is a formulation of this concept that contribute to the understanding of what we see and what we expect in the possible space of network configurations.
Mathematical modelling of biomolecular and cellular processes.
Biological systems cannot be understood with the
arrow of time. Computational and mathematical models are the work-bench
for the working hypotheses formulation that, in combination with
experiments, provide a deep understanding of biological phenomena. Any
model is a simplification of reality that responds to different
needs. When enough data is acessible, the construction of full
descriptive models seeks the accurate prediction of study
systems. However, such a models becomes highly understandable due
to their high number of parameters and processes. By contrast, minimal
models offers a simple but a very helpful approach for the
understanding of the principles of organisation in complex behaviours
in a qualitative way.
Following the approach of descriptive models my research contribution
has focussed on the study and analysis of metabolic pathways.
Simple model approach has permited to me to get insight obout more
general processes such as the role of task distribution in the
organisation of tissue organization.
