Caspo: A toolbox for automated reasoning on the response of logical signaling networks families

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Abstract

We introduce the caspo toolbox, a python package implementing a workflow for reasoning on logical networks families. Our software allows researchers to (i) learn a family of logical networks derived from a given topology and explaining the experimental response to various perturbations; (ii) classify all logical networks in a given family by their input-output behaviors; (iii) predict the response of the system to every possible perturbation based on the ensemble of predictions; (iv) design new experimental perturbations to discriminate among a family of logical networks; and (v) control a family of logical networks by finding all interventions strategies forcing a set of targets into a desired steady state.

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Videla, S., Saez-Rodriguez, J., Guziolowski, C., Siegel, A., & Wren, J. (2017). Caspo: A toolbox for automated reasoning on the response of logical signaling networks families. Bioinformatics, 33(6), 947–950. https://doi.org/10.1093/bioinformatics/btw738

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