Computational reconstruction of biochemical networks

Biochemical networks are hierarchical complex systems involving many heterogeneous molecular species and intricate mechanisms such as crosstalks between different pathways and emergent dynamic behaviour. Computational modelling and simulation have proved to be powerful new approaches to the investigation of such complex systems. Modelling and simulation initially require the reconstruction in silico of the biochemical system in question using experimental datasets and complementary sources. While all reconstruction projects are to some extent unique, they can all be characterized by specific research questions, data/knowledge requirements, computational expertise, etc. To date, no single approach can be applied successfully to all biochemical reconstruction efforts. Moreover, no guidelines have yet been proposed to guide investigator through this process. Here we attempt to address this gap by providing a comprehensive overview of the reconstruction methods commonly applied to biochemical networks. We evaluate the principal methods of computational reconstruction with regards to data availability and type, target system scale, research/study aims and computational requirements.