The informative value of biomolecular networks has shifted from being solely information resources for possible cellular partners (whether these embody proteins, (ribo)nucleic acids or small molecules) towards becoming models for the functional connectivity within a cell. These models are increasingly exploited to make quantitative predictions about the cell’s functional organization as well as about the functionality of individual elements in the network.
A large number of concepts and methods have been proposed in order to interpret experimental data mapped to cellular networks these systems and to make use of the rich source of information they represent.
We will present a system for the Comprehensive Analysis of Biomolecular Networks (CABiNet), capable of integrating available network analysis methods. Integration is done by classifying each method into one of four separate categories using standardized interfaces that encapsulate the functionality of the method in a distinct component with standardized in- and output. These components can be accessed individually or in an integrated form using a processing pipeline for semi-automatic analyses.
Additionally, the system can be used to query both biomolecular networks as well as the derived results of network analysis methods, such as clustering algorithms, in order to provide a service for researchers who are focused towards the functional context of any particular cellular entity.
CABiNet is designed in an easy-to-use and easy-to-extend software framework that allows a straightforward integration of novel components. We will demonstrate the capabilities of the system by introducing several use cases.
The CABiNet suite can be accessed at http://mips.gsf.de/genre/proj/CABiNet. Source code including additional components that can be accessed using the API is available upon request.