Sabine Dietmann, Daniel Aguilar, Michael Mader, Matthias Oesterheld, Andreas Ruepp, Volker Stuempflen and Hans-Werner Mewes Pages 3723 - 3734 ( 12 )
Molecular databases serve as primary information resources for the analysis of biological networks providing an essential and invaluable treasure for information exploration. Tools for projecting experimental data sets onto known functional information are a major need to support the analysis of samples produced in clinical research. A new concept is the notation of functional modules, i.e. the characterisation of sets of proteins that perform a defined biological function in cooperation. The determination and analysis of functional modules overcome the limitations of the analysis of individual genes and their properties. Although functional modules are not suitable to fully capture systems properties, they have the potential to unify the information generated by different types of experiments. We describe advances related to the problem of integrating heterogeneous data sets into functional modules for mouse and/or human cellular networks based on publicly available data resources, including advances in the design of ontologies for functional classification, problems of automatic protein functional annotation and integration of microarray data.
Functional modules,function annotation,ontologies,protein interaction networks,clustering algorithms,microarray data