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Abstract:
Biological system modeling is an iterative process where un-
certainties may arise, especially in the early stages of the modeling.Static analysis tools are needed during each stage of the modeling to help modelers detect unexpected behaviors early by automatically inferring properties about the model. However, the rule-based modeling language Kappa and its static analysis tool KaSa currently lack support for incomplete models.
In this work, we extend Kappa to support incomplete models, where
some rules are considered or not depending on the value of some boolean
parameters. We also generalize the current reachability analysis of the
static analyzer KaSa to these parametric models, establishing relationships between properties and parameter values. Finally, we implement and evaluate our approach on example models.
@InProceedings{10.1007/978-3-032-01436-8_9, author="Feret, J{\'e}r{\^o}me and Ghidini, Rebecca", editor="Fages, Fran{\c{c}}ois and P{\'e}r{\`e}s, Sabine", title="Reachability Analysis for Parametric Rule-Based Models", booktitle="Computational Methods in Systems Biology", year="2026", publisher="Springer Nature Switzerland", address="Cham", volume="15959", pages="153--173", isbn="978-3-032-01436-8" }