Name | biomass JSON |
Version |
0.12.0
JSON |
| download |
home_page | |
Summary | A Python Framework for Modeling and Analysis of Signaling Systems |
upload_time | 2023-05-05 08:37:39 |
maintainer | |
docs_url | None |
author | Hiroaki Imoto |
requires_python | >=3.8 |
license | Apache-2.0 |
keywords |
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bugtrack_url |
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requirements |
No requirements were recorded.
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Travis-CI |
No Travis.
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coveralls test coverage |
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<br>
<p align="center">
<a href="https://biomass-core.readthedocs.io/en/latest">
<img src="https://raw.githubusercontent.com/biomass-dev/biomass/master/docs/_static/img/biomass-logo.png" width="400">
</a>
</p>
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_BioMASS_ is a computational framework for modeling and analysis of biological signaling systems in Python.
- **Documentation:** https://biomass-core.rtfd.io
- **Source code:** https://github.com/biomass-dev/biomass
- **Bug reports:** https://github.com/biomass-dev/biomass/issues
- **Citing in your work:** https://biomass-core.rtfd.io/en/latest/citing.html
It provides useful tools for numerical simulation, parameter estimation, network analysis, and result visualization.
## Installation
The BioMASS library is available at the [Python Package Index (PyPI)](https://pypi.org/project/biomass).
```shell
$ pip install biomass
```
BioMASS supports Python 3.8 or newer.
## References
- Imoto, H., Zhang, S. & Okada, M. A Computational Framework for Prediction and Analysis of Cancer Signaling Dynamics from RNA Sequencing Data—Application to the ErbB Receptor Signaling Pathway. _Cancers_ **12**, 2878 (2020). https://doi.org/10.3390/cancers12102878
- Imoto, H., Yamashiro, S. & Okada, M. A text-based computational framework for patient -specific modeling for classification of cancers. _iScience_ **25**, 103944 (2022). https://doi.org/10.1016/j.isci.2022.103944
## Author
[Hiroaki Imoto](https://github.com/himoto)
## License
[Apache License 2.0](https://github.com/biomass-dev/biomass/blob/master/LICENSE)
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