Welcome

Cellnition is an open source simulator to create and analyze Network Finite State Machines (NFSMs) from regulatory network models.

Regulatory networks, such as Gene Regulatory Networks (GRNs), preside over so many complex phenomena in biological systems, yet given a specific regulatory network, how do we know what it's capable of doing?

Cellnition aims to provide a detailed answer to that question, by treating regulatory networks as analogue computers, where NFSMs map the sequential logic, or analogue "software program", inherent in the regulatory network's dynamics.

NFSMs have a range of potential applications, including facilitating the identification of potential strategies to renormalize cancer.

Installation

Cellnition is installable with pip, the standard package installer officially bundled with Python:

pip install cellnition

Issues

Please use the Cellnition issue tracker to report any problems or feedback pertaining to the codebase.

About

Read more about Cellnition's NFSMs in our pre-print publication: Harnessing the Analogue Computing Power of Regulatory Networks with the Regulatory Network Machine.

Please cite our publication in any work that utilizes Cellnition:

Pietak, Alexis, and Michael Levin.
 “Harnessing the Analog Computing Power of Regulatory Networks 
 with the Regulatory Network Machine.” OSF Preprints, 2 Dec. 2024. Web.

Cellnition is portably implemented in Python, continuously stress-tested via GitHub Actions × tox × pytest × Codecov, and licensed under a non-commercial use, open source APACHE license with Tufts Open Source License Rider v.1. For maintainability, cellnition officially supports only the most recently released version of CPython.

Acknowledgements

Cellnition creator Alexis Pietak is grateful for collaboration opportunities and funding support from the Levin Lab at Tufts University, via a Templeton World Charity Foundation grant 0606. Thanks goes out to Brian Curry for his volunteer assistance with the Cellnition code repository.

Disclaimer

Alexis Pietak created Cellnition, and co-authored the associated scientific manuscript, as an external contractor ("Affiliate Research Scientist") for Tufts University. Under the established terms of Tufts University, as an external contractor, Alexis receives no royalties nor other financial benefits or entitlements in connection with any intellectual property associated with the Cellnition project or its associated scientific manuscript.

Note that the functionality provided and work presented in Cellnition and its associated scientific manuscript are at a theoretical and computational stage, with any and all potential applications for the work requiring verification by real world experiments and by comprehensive testing.

License

Cellnition is non-commerical use open source software licensed under an Apache 2.0 license with Tufts Open Source License Rider v.1, restricting use to academic purposes only.