Reasoning on the response of logical signaling networks with Answer Set Programming
Reasoning on the response of logical signaling networks
The manual identification of logic rules underlying a biological system is often hard, error-prone and time consuming. Further, it has been shown that, if the inherent experimental noise is considered, many different logical networks can be compatible with a set of experimental observations. Thus, automated inference of logical networks from experimental data would allow for identifying admissible large-scale logic models saving a lot of efforts and without any a priori bias. Next, once a family a logical networks has been identified, one can suggest or design new experiments in order to reduce the uncertainty provided by this family. Finally, one can look for intervention strategies that force a set of target species or compounds into a desired steady state. Altogether, this constitutes a pipeline for automated reasoning on logical signaling networks. Hence, the aim of caspo is to implement such a pipeline providing a powerful and easy-to-use software tool for systems biologists.
Detailed documentation about how to install and use caspo is available at http://caspo.readthedocs.io.
Sample files are included with caspo and available for download
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|Filename, size & hash SHA256 hash help||File type||Python version||Upload date|
|caspo-3.0.1-py2-none-any.whl (63.5 kB) Copy SHA256 hash SHA256||Wheel||py2||Oct 5, 2016|
|caspo-3.0.1.tar.gz (979.1 kB) Copy SHA256 hash SHA256||Source||None||Oct 5, 2016|