The multi-disciplinary approach of systems biology combines a variety of modern experimental techniques which lead to an increased accuracy of measurements of enzyme structures and activities by the application of advanced analysis methods.
Due to these technological inventions in turn huge amounts of data and large data sets are generated and subsequently published in electronic data repositories and in written papers. However, all these data in both the literature and in databases suffer from the fact that they are incomparable due to incomplete and fragmented descriptions of materials and methods, and therefore are, to some extent, unreliable. Furthermore, if the experimental conditions are not clearly and fully stated, the values of the functional data of enzyme activities are of little use for, in particular, systems biology applications.
Moreover, experimental results have been collected under quite disparate conditions so that researchers often are faced with the problem of the range of method-specific enzyme data. This causes problems when data move between researchers whose data are supplied by laboratories that use different methods, and can, in the worst case, lead to misinterpretations of laboratory findings.