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Phototrophic Biofilms

Aquatic microbial communities composed of photosynthesizing algae, bacteria, and an extra-cellular biopolymer matrix holding a so-called biofilm together, are found on any submerged surfaces exposed to sunlight. To get deeper insight into the complex structure, composition, and physiology of these micro-communities, extensive experimental studies are combined with computational tools within the EU-project PHOBIA. The research activities in this group yield three principal contributions to that endeavour: i) PHLIP, an open-source project to quantify biofilm morphology, ii) WebPHOBIA, an online data repository for all experimental outputs from PHOBIA, and iii) a unifying model, based on artifical neural networks, in order to detect important relations between the experimental observables, and allow predictions for new experimental approaches. Within this frame, potential applications in wastewater treatment and anti-biofouling are explored as well.

Biological Sequence Analysis

The goal is to develop theory and algorithms to interpret the wealth of data becoming available in public genomic and proteomic databases. The use of Chaos Theory, namely Iterative Maps, is being explored to extend the conventional Hidden Markov modeling (HMM) techniques.

Epidemiology

EURIS is a 3-year long pan-european epidemiological research project aimed at antibiotic-resistant S. pneumoniae carriage in Day Care Centers. Due to its dimension, duration, medical importance, geographical diversity, large amounts of data will be generated that require both immediate and deeper analysis. The EURIS project is therefore taken as a model for data gathering, management and analysis, in epidemiological / biological studies by several independent research groups. Online accessible software will be made for the several stages of the project, making it possible for different participants to have the benefits of a database and statistic packages on a user-friendly interface only requiring a web-browser. The data will be further analysed by means of several methodologies, modelling techniques, and artificial inteligence algorithms. We hope to find the infection routes and resistance selective pressures (risk factors) that most contribute to the alarming increase of antibiotic-resistant S.pneumoniae carriage in young children.

Nonlinear Time Series Analysis

Complexity theory establishes that biological units, such as organisms or ecosystems, are self-ordering entities, characterised by internal networking and multiple feedback loops. They represent dissipative structures, which require not only energy but also information to retain their organised structure. The quantification of organisational properties of the system and their subsequent association with the structure of the biological community is based on four measures: active degrees of freedom (correlation dimension), uncertainty (Kolmogorov-Sinai entropy), instability (Lyapunov exponents) and statistical complexity (excess entropy).