GBF - German Research Center for Biotechnology (GBF),
Res. Group Bioinformatics,
Mascheroder Weg 1b,
D-38124 Braunschweig, Germany;
Email: kse@gbf.de
The development and maintenance of a functional organism is based on a multitude of successive events organizing a network of regulatory systems, that in concerted actions ensure the balance of life. Disturbance of this balance results in a breakdown of distinct regulatory units followed by malfunction or even the death of the organism. Many of the acquired or innate diseases can be traced back to the failure of particular gene functions and the subsequent disarrangement of biological circuits during embryonic development. In order to model the effects of genetic variations on cell specific as well as systemic networks, the relational genotype/phenotype platform PheGe was generated. PheGe enables recording and evaluation of pathological relevant data and finally permits the coordination of the aberrant genes and gene products into the various regulatory pathways balancing phenotypic patterns.
The basic units of PheGe are the molecules, which are linked to their cellular sources, and to the cell-specific reactions in which they take part. The reactions are organized in a way that enables tracking of specific pathways from the binding of a ligand to its receptor on the cell surface towards the generation of new gene products which assert their effects either locally or in an autocrine, paracrine or endocrine fashion. According to the various modes of molecule's action, a reaction sorter (multi-level pathway builder; MLPB) was generated. This powerful tool not only hierarchically sorts and coordinates the various molecules and reactions to their particular signaling systems, but also organizes downstream events on a multi-cellular level. Moreover, PheGe enables modeling of cellular differentiation during morphogenesis and traces network components that balance differentiation programs.
A central module of PheGe is Pathopath. Pathopath is a relational database that collects information about pathological alterations of signal transduction components and the corresponding phenotypes. Together with MLPB it enables visualization of altered pathway components and the consequences for downstream events. The incorporation of pathological relevant data and their downstream effects into the virtual world of signal transduction creates a new quality for the evaluation of reaction patterns within regulatory networks. It will light up the meaning of individual network components for genesis and maintenance of particular phenotypes. Within the huge accumulation of information concerning genotype/phenotype correlations the computational modeling and simulation of regulatory networks targets new impulses for basic sciences.