BioASP is a collection of open-source programs, providing solutions for analyzing biological data and models with Answer Set Programming (ASP). ASP has proven to be an excellent tool for solving a variety of biological questions. The BioASP applications implement methods for analyzing metabolic, signaling and gene regulatory networks, consistency checking, diagnosis, and repair of biological data and models. In particular, it allows for computing predictions and generating hypotheses about required extensions of biological models, as well as designing new experiments and finding intervention strategies to control the biological system at hand.
BioASP is powered by the ASP tools of Potassco, the Potsdam Answer Set Solving Collection. The functionalities provided by the BioASP applications exploit technical know-how of modeling (biological) problems in ASP and gearing ASP solvers’ parameters to them. BioASP applications integrate our practical experience and offers them via easy-to-use Python functions, thus enabling ASP non-experts to solve biological questions with ASP.
- meneco - Metabolic network completion
- precursor - Compute minimal metabolic precursors
- caspo - Reasoning on the response of logical signaling networks
- caspots - Boolean network inference from time series data with perturbations
- ExDesi - Experiment planning to discriminate influence graph models
- iggy - Consistency of influence graphs models and observed systems behaviors
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