Problem solving by inverse methods in systems biology [Invited paper abstract]

Systems biology is heading for the ambitious goal to model cells and organisms as integral entities by the methods of chemistry and physics. A hierarchy of levels of description is required ranging from chemical kinetics at the molecular level up to the interaction of cell organelles within the cell or organs within the organism. A true wealth of data is produced by the various 'omics' approaches from genome sequencing to protein interactions and signaling and eventually to functional genomics dealing with the role of molecules and supra-molecular complexes in the well-organized concerted actions of parts within higher unities. Data are available and models have been conceived, but the relation of data and model parameters is still not very well understood. The application of inverse methods might be very helpful: Two different levels of inverse methods techniques are conceivable: (i) parameter estimation for data and (ii) reverse engineering of model behavior from known parameters. Examples of both approaches will be discussed in the lecture.