SCAN: Integrative computational approaches in biosystems research

Abstract

To produce organized knowledge from data generated by modern technologies, from molecular biology to satellite remote-sensing, experimental work in life sciences is increasingly accompanied with theoretical and computational methods for data management, analysis and simulations. A recent interdisciplinary approach aiming at the enhancement of this convergence is Systems Biology. In the present work, its integrative aspects are illustrated with examples from ongoing research at the Systems Biodynamics Group at ITQB.

i) Combining the analysis of image-series of the photosynthetic metabolism in a plant leaf with simulations of systems of coupled oscillators, the effecs of heterogeneous environmental signals on the synchronization of biological rhythms are studied. This example demonstrates how the integration of modeling and data analysis may help to assist experimental efforts and foster the achievement of systems knowledge.
ii) With the example of a European multi-partner project on phototrophic biofilms approaches and challenges to integrating heterogeneous ecophysiological data sets from different laboratories are discussed. The predictive modeling of the stochastic growth of biofilm biomass as one endpoint of this study is highlighted.

It will be claimed that computational tools can significantly support interdisciplinary team research by the enhancing the efficiency of the communication between the team members, but are no means to completely substitute personal interactions. Potential ways of how these approaches could be connected to ongoing experimental work at ITQB will be sketched.