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Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance

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tidysbml: R/Bioconductor package for SBML extraction into dataframes.

Veronica Paparozzi¹, Christine Nardini¹

¹Institute for Applied Mathematics (IAC) "Mauro Picone", National Research Council (CNR), Rome 00185, Italy.

Bioinformatics Advances

|October 16, 2024

Summary

This summary is machine-generated.

The tidysbml R package simplifies extracting biological data like compartments, species, and reactions from Systems Biology Markup Language (SBML) files. This facilitates network construction and analysis using popular R packages.

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Area of Science:

Systems Biology
Bioinformatics
Computational Biology

Background:

Systems Biology Markup Language (SBML) is a standard for representing biochemical models.
Extracting data from SBML files into usable formats can be challenging for analysis.
Biological network construction and analysis require efficient data handling.

Purpose of the Study:

To introduce tidysbml, an R package for extracting data from SBML files.
To provide a user-friendly method for accessing compartments, species, and reactions.
To facilitate the construction and analysis of custom biological networks.

Main Methods:

Developed an R package named tidysbml.
Implemented functions for parsing SBML documents (up to Level 3).
Output data in tabular structures (R dataframes) for easy manipulation.

Main Results:

Successfully extracts compartment, species, and reaction data from SBML files.
Generated tabular data structures compatible with R's data manipulation tools.
Demonstrated exemplar data extraction from Reactome SBML files.

Conclusions:

tidysbml simplifies data extraction from SBML, enhancing biological information accessibility.
The package supports downstream network analysis through integration with R packages like igraph and RCy3.
tidysbml offers a valuable tool for systems biology research and custom network construction.