Using process diagrams for the graphical representation of biological networks

Area of Science:

• Systems Biology
• Bioinformatics
• Computational Biology

Background:

• Growing interest in biological networks (protein-protein interaction, gene regulatory) necessitates improved representation methods.
• Existing machine-readable formats like Systems Biology Markup Language (SBML) are advanced, but human-readable representations have lagged.
• Effective communication of complex biological network data is crucial for research advancement.

Purpose of the Study:

• To address the gap in human-readable representations of biological networks.
• To propose a novel set of diagrammatic notations that improve formality and information richness.
• To facilitate straightforward translation of visual network representations into machine-readable formats like SBML.

Main Methods:

• Discussion of human-readable diagrammatic representations.
• Proposal of a new set of formal notations for biological networks.
• Utilizing a state transition-based process diagram model.
• Support and application within CellDesigner software.

Main Results:

• Development of a diagrammatic notation enhancing biological network representation.
• Demonstrated straightforward translation of the proposed diagrams into machine-readable formats (e.g., SBML).
• Successful application of the notation to diverse biological networks of varying scales using CellDesigner.

Conclusions:

• The proposed diagrammatic notation enhances both human comprehension and machine readability of biological networks.
• This approach offers a valuable tool for researchers, bridging the gap between visual representation and computational analysis.
• The integration with CellDesigner and SBML compatibility promotes wider adoption and application in systems biology research.