Alias4SBML: A Python Package for Generating Alias Nodes in SBML Models
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866909496479055872 |
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| author | Heydarabadipour, Adel Sauro, Herbert M |
| author_facet | Heydarabadipour, Adel Sauro, Herbert M |
| contents | Interpreting biological networks becomes challenging when molecular components, such as genes or proteins, participate in numerous interactions, resulting in densely connected regions and overlapping interactions that obscure functional relationships and biological insights. To address this, we introduce Alias4SBML, a Python package that enhances SBML model visualizations by generating alias nodes-duplicate representations of highly connected molecular components-to redistribute interactions and reduce visual congestion. Applying Alias4SBML to the SBML models, including one with 59 species and 41 reactions and another with 701 species and 505 reactions, demonstrated significant improvements in readability, with edge length reductions of up to 50.88 %. Our approach preserves the structural integrity of the network while facilitating clearer interpretation of complex biological systems, offering a flexible and scalable solution for visualizing biological models more efficiently. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2502_11318 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Alias4SBML: A Python Package for Generating Alias Nodes in SBML Models Heydarabadipour, Adel Sauro, Herbert M Molecular Networks Interpreting biological networks becomes challenging when molecular components, such as genes or proteins, participate in numerous interactions, resulting in densely connected regions and overlapping interactions that obscure functional relationships and biological insights. To address this, we introduce Alias4SBML, a Python package that enhances SBML model visualizations by generating alias nodes-duplicate representations of highly connected molecular components-to redistribute interactions and reduce visual congestion. Applying Alias4SBML to the SBML models, including one with 59 species and 41 reactions and another with 701 species and 505 reactions, demonstrated significant improvements in readability, with edge length reductions of up to 50.88 %. Our approach preserves the structural integrity of the network while facilitating clearer interpretation of complex biological systems, offering a flexible and scalable solution for visualizing biological models more efficiently. |
| title | Alias4SBML: A Python Package for Generating Alias Nodes in SBML Models |
| topic | Molecular Networks |
| url | https://arxiv.org/abs/2502.11318 |