Analysing Cell Line Specific EGFR Signalling via Optimized Automata Based Model Checking

Building models with a high degree of specificity, e.g. for particular cell lines, is becoming an important tool in the advancement towards personalised medicine. Constraint-based modelling approaches allow for utilizing general system knowledge to generate a set of possible models that can be further filtered with more specific data. Here, we exploit such an approach in a Boolean modelling framework to investigate EGFR signalling for different cancer cell lines, motivated by a study from Klinger et al. [8]. To optimize performance of the underlying model checking procedure, we present a number of constraint encodings tailored to describing common data types and experimental set-ups. This results in a significant increase in the performance of the approach.

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