Scientists have been in a quandary about definitions of Systems Biology for the past few years. These range from collections of physiological data with quantified molecular parts lists (e.g. genes, expression levels, localizations) to abstract mathematical modelling of biological processes.  The scale at which Systems Biology focuses is also a matter of contention:  A tiny protein can be a complicated biological system (we still don’t know how it folds) as is obviously an entire ecosystem with thousands of species.  The term “Systems Biology” will probably soften even further as it is now under the limelight and funding opportunities have to be taken seriously by very diverse scientific communities.  Thus Systems Biology encompasses many different aspects starting with standardised data collection, archiving and management.  This data then needs to be integrated to allow for comparative evaluation (comparative genomics and proteomics). Once that is done we need an idealized reconstruction of the experimental situation close to reality by using computer modeling.  Based on this modeling exercise new experiments can be designed and new insights obtained.  Finally experimental testing of the model closes the circle and feedbacks on the whole procedure.

At the CRG we have a strong Biocomputing programme that could cover the data gathering and the comparative genomics, thus in our programme we will put more emphasis on data integration, computer modeling and experimental validations as well as on the design aspect.  In these aspects we will establish strong links with the Gene regulation, cancer and cell biology and development programmes.  We expect that a systematic analysis of biological systems will allow us new insights in human diseases and for this string ties should be made with the Gene and Diseases programme.