Abstract
In this paper we present two approaches, namely correlative and static causality, to study cause-effect relationships in reaction models and we propose a framework which integrates them in order to study causality by means of transition P systems. The proposed framework is based on the fact that statistical analysis can be used to building up a membrane model which can be used to analyze causality relationships in terms of multisets of objects and rules in presence of non-determinism and parallelism. We prove that the P system which is defined by means of correlation analysis provides a correspondence between the static and correlative notions of causality.
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