Strategic Research Computational Biology and Complex Systems Group (BIOCOM-SC)

Computational Biology and Complex Systems Group (BIOCOM-SC)

The Computational Biology and Complex Systems group is a consolidated group recognized by the Catalan Government (Generalitat de Catalunya, ref. 2014SGR-1093). The aim of the group is the use of computational methods to address complex problems in biomedicine and biophysics. In the last years we have addressed problems in cardiac dynamics, computational neuroscience, epidemiology, cell biophysics, development of infectious diseases (tuberculosis, chagas), or engineering of biosystems for environment and food technology applications. To address these problems we use a variety of computational techniques, including simulations of partial, ordinary and stochastic differential equations, or agent-based (ABM) and individual-based modelling (IBM).

Main projects

  • 1.

    Biophysics of polarity and amoeboid motion of living cells

    We construct a mathematical model to study the interplay between spontaneous cell polarization, internal stochasticity and spontaneous and chemotactic cellular locomotion. In particular we consider the motion of the amoeba Dictyostelium discoideum, which under starvation moves randomly seeking for food. We compare and fit the model to experimental data to obtain realistic deformations and velocities.

  • 2.

    Development and application of atrial myocyte models to investigate mechanims that confer patients a high risk of atrial fibrillation

    We use detailed mathematical models of atrial myocytes at tissue, cellular and subcellular scales to study the effect of genetic variants in the probability of suffering atrial fibrillation. We pay special attention to dysfunctions in calcium handling, including calcium alternans and the occurrance of spontaneous calcium waves.

  • 3.

    IMultiscale computational modelling of tuberculosis

    Tuberculosis (TB) is the disease that causes more deaths worldwide after AIDS. We use mathematical modeling as a tool to help cope with the challenges of TB. The objective of this project is to model various systems corresponding to different spatial scales (basically cultures in vitro and ex vivo methods, dynamic lung lesions in animal models and humans, and transmission of TB in cities and countries). The systems under study are composed of units that determine their behavior, from cells in vitro, to cultures granulomas in the lungs or people at the epidemiological scale. The diversity of properties in the units within a system and their interactions raise the emergent behavior of those systems. Thus, agent-based (ABM) and individual-based modeling (IBM) are mainly used for their study.



Bioinformatics expertise:

Group Leader:

Blas Echebarria Dominguez