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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.19046 |
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| _version_ | 1866916025105121280 |
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| author | Monteiro, Pedro T. Gouveia, Filipe |
| author_facet | Monteiro, Pedro T. Gouveia, Filipe |
| contents | Biological regulatory networks can be represented by computational models, which allow the study and analysis of biological behaviours, therefore providing a better understanding of a given biological process. However, as new information is acquired, biological models may need to be revised in order to also account for this new information. Current model revision tools are scarce and often lack the flexibility to integrate with broader analysis workflows. Here, we present pyModRev, an enhanced iteration of the model revision tool ModRev, capable of verifying the consistency of Boolean regulatory models, and finding minimal repairs in case of inconsistency. pyModRev supports model validation against both steady state observations as well as time-series data, being able to consider different update schemes simultaneously. pyModRev supports different model formats, and is available as a Python package in PyPI, for easy integration with other model analysis tools, significantly improving accessibility and utility for the logical modelling community. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_19046 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | pyModRev: a Python Tool for Model Revision of Boolean Networks Monteiro, Pedro T. Gouveia, Filipe Computational Engineering, Finance, and Science Biological regulatory networks can be represented by computational models, which allow the study and analysis of biological behaviours, therefore providing a better understanding of a given biological process. However, as new information is acquired, biological models may need to be revised in order to also account for this new information. Current model revision tools are scarce and often lack the flexibility to integrate with broader analysis workflows. Here, we present pyModRev, an enhanced iteration of the model revision tool ModRev, capable of verifying the consistency of Boolean regulatory models, and finding minimal repairs in case of inconsistency. pyModRev supports model validation against both steady state observations as well as time-series data, being able to consider different update schemes simultaneously. pyModRev supports different model formats, and is available as a Python package in PyPI, for easy integration with other model analysis tools, significantly improving accessibility and utility for the logical modelling community. |
| title | pyModRev: a Python Tool for Model Revision of Boolean Networks |
| topic | Computational Engineering, Finance, and Science |
| url | https://arxiv.org/abs/2605.19046 |