Editorial

Abstract

Several years ago the analysis of the human genome was resulting in the disappointing finding that humans have only about 30 000 genes compared to expected 100 000 ones. Now only 25 000 genes are estimated. This finding made clear that the control of organismic structures and functions can only be understood by the multi-component analysis of genomic actions. Additionally, new analytical high-throughput technologies such as DNA microarrays provided a huge amount of data on gene expression that can not be understood by classical mathematical tools. Instead of this, besides multivariate statistics also graph theoretical approaches and genetic programming are promising tools for analysis of complex data sets. The necessity of using mathematical tools in molecular biology in the late 1990s and early 2000s were summarized with the terms “computational molecular biology”. Additionally, in order to understand the functions of the various biomolecules in the cellular and supracellular context the approach of systems thinking was proposed by Kitano with the term “Systems biology”. This approach aims to construct a cell on the level of a computerized mathematical model. This “in-silico-modelling” allows studying the behaviour of complex dynamic systems under various conditions. With these results new experiments in the “wet” laboratory can be performed. New data should allow modifications of the model and so the cycle of scientific knowledge is proceeding.