The analysis of biological data asks for a delicate balance of content-specific and procedural knowledge; this is why it is virtually impossible to apply standard mathematical and statistical recipes to systems biology.The separation of the important part of information from singular (and largely irrelevant) details implies a continuous interchange between biological and statistical knowledge. The generalization ability of the models must be the principal focus of system's parameter estimation, while the multi-scale character of biological regulation orients the modeling style toward data-driven strategies based on the correlation structure of the analyzed systems.
Keywords: Biological regulation; Overfitting; Principal component analysis; Soft modeling.