| Autor: |
Adam Šmelko, Miroslav Kratochvíl, Emmanuel Barillot, Vincent Noël |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-15 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
1471-2105 |
| DOI: |
10.1186/s12859-024-05815-5 |
| Popis: |
Abstract Background Computational models in systems biology are becoming more important with the advancement of experimental techniques to query the mechanistic details responsible for leading to phenotypes of interest. In particular, Boolean models are well fit to describe the complexity of signaling networks while being simple enough to scale to a very large number of components. With the advance of Boolean model inference techniques, the field is transforming from an artisanal way of building models of moderate size to a more automatized one, leading to very large models. In this context, adapting the simulation software for such increases in complexity is crucial. Results We present two new developments in the continuous time Boolean simulators: MaBoSS.MPI, a parallel implementation of MaBoSS which can exploit the computational power of very large CPU clusters, and MaBoSS.GPU, which can use GPU accelerators to perform these simulations. Conclusion These implementations enable simulation and exploration of the behavior of very large models, thus becoming a valuable analysis tool for the systems biology community. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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