Structural and Functional Analysis of Cellular Networks
CellNetAnalyzer (CNA) is a MATLAB toolbox providing a graphical user interface and various (partially unique) computational methods and algorithms for exploring structural and functional properties of metabolic, signaling, and regulatory networks. Computations can be started within the GUI (interactive network maps) or from command line (via API functions).
Metabolic networks are formalized and analyzed by stoichiometric and constraint-based modeling techniques, including flux balance analysis (FBA), metabolic flux analysis, elementary-modes analysis, minimal cut set analysis, and many more. Several algorithms are provided for computational strain design / metabolic engineering.
Signal transduction and (gene) regulatory networks are represented in CNA as logical networks (both Boolean and multivalued logic are supported) or/and as interaction graphs. Among other features, CNA supports logical steady state analysis (e.g., for studying the input-output behavior of signaling networks), the computation of minimal intervention sets enforcing or blocking certain behaviors, discrete simulations of Boolean models as well as simulation of logic-based ODEs derived from Boolean models (via ODEfy plugin). Methods for studying properties of interaction graphs include enumeration and analysis of feedback loops and signaling paths as well as analysis of global interdependencies.
CellNetAnalyzer is part of de.NBI (the German Network for Bioinformatics Infrastructure) and we offer extended services and training courses for interested users.
We also refer interested users to CNApy (CellNetAnalyzer for Python), which is a cross-platform desktop application written in Python for constraint-based analysis of metabolic networks. While the basic look-and-feel of CNApy is similar to the CellNetAnalyzer user interface, it provides a more advanced graphical front-end with enhanced GUI features for metabolic modeling.