{"title":"tidysbml: R/Bioconductor package for SBML extraction into dataframes.","authors":"Veronica Paparozzi, Christine Nardini","doi":"10.1093/bioadv/vbae148","DOIUrl":null,"url":null,"abstract":"<p><strong>Summary: </strong>We present <i>tidysbml</i>, an R package able to perform <i>compartments</i>, <i>species</i>, and <i>reactions</i> data extraction from Systems Biology Markup Language (SBML) documents (up to Level 3) in tabular data structures (i.e. R dataframes) to easily access and handle the richness of the biological information. Thanks to its output format, the package facilitates data manipulation, enabling manageable construction, and therefore analysis, of custom networks, as well as data retrieval, by means of R packages such as <i>igraph</i>, <i>RCy3</i>, and <i>biomaRt</i>. Exemplar data (i.e. SBML files) are extracted from Reactome.</p><p><strong>Availability and implementation: </strong>The <i>tidysbml</i> R package is distributed under CC BY 4.0 License and can be found publicly available in Bioconductor (https://bioconductor.org/packages/tidysbml) and on GitHub (https://github.com/veronicapaparozzi/tidysbml).</p>","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"4 1","pages":"vbae148"},"PeriodicalIF":2.4000,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11479578/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics advances","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/bioadv/vbae148","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
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Abstract
Summary: We present tidysbml, an R package able to perform compartments, species, and reactions data extraction from Systems Biology Markup Language (SBML) documents (up to Level 3) in tabular data structures (i.e. R dataframes) to easily access and handle the richness of the biological information. Thanks to its output format, the package facilitates data manipulation, enabling manageable construction, and therefore analysis, of custom networks, as well as data retrieval, by means of R packages such as igraph, RCy3, and biomaRt. Exemplar data (i.e. SBML files) are extracted from Reactome.
Availability and implementation: The tidysbml R package is distributed under CC BY 4.0 License and can be found publicly available in Bioconductor (https://bioconductor.org/packages/tidysbml) and on GitHub (https://github.com/veronicapaparozzi/tidysbml).
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