Closing the gap between formats for storing layout information in systems biology

Area of Science:

• Systems Biology
• Bioinformatics
• Computational Biology

Background:

• Complex biological networks require specific layouts and topologies for understanding.
• Currently, three main layout-aware systems biology formats exist, but no single tool supports all.
• This lack of interoperability hinders the management, reuse, and extension of molecular network data.

Purpose of the Study:

• To provide an overview of layout formats in systems biology, highlighting commonalities and differences.
• To review existing software support for these formats.
• To introduce a new conversion module within the MINERVA platform to address format incompatibility.

Main Methods:

• High-level overview and comparative analysis of layout-aware systems biology formats.
• Review of current software tools, libraries, and repositories supporting these formats.
• Development and integration of a conversion module with a REST API into the MINERVA platform.

Main Results:

• Identified challenges in managing and reusing molecular network layouts due to format fragmentation.
• Developed a novel conversion module supporting multiple layout-aware systems biology formats.
• The module facilitates conversion between formats and export to various graphical formats via a REST API.
• Demonstrated capability to handle very large networks, including disease maps and metabolic reconstructions.

Conclusions:

• The new MINERVA conversion module enhances interoperability for layout-aware systems biology formats.
• It simplifies the management, reuse, and extension of molecular network data.
• The tool's applicability extends to large-scale biological network analyses in systems biology.