Bioinformatics and Computational Biology at the crossroads of post-genomic technology

Abstract

The traditional approach of experimental biology is strongly based on the analysis of the individual components, genes and proteins. In this case bioinformatics methods are essential for the organization of the information in databases and for the interconnection of the accumulated knowledge. This classical approach is now complemented by the vision provided by the new techniques in genomics and proteomics that are generating a large set of complex data. These data include gene-control networks derived from experiments with expression arrays, protein interaction networks derived from the application of proteomics and prediction methods, and metabolic networks derived from systematic metabolomic approaches. One of the more interesting outcomes of this information is the possible description of cellular systems at the level of interactions between genes and proteins. Bioinformatics and computational Biology are the appropriated reference framework for the study of these interaction networks. Two of the avenues that are currently explored are the prediction of function based on the information from neighbour genes and proteins with well-characterized functions, and the first steps toward the simulations of defined cellular systems.