Concurrency in leukocyte vascular recognition: developing the tools for a predictive computer model

Leukocyte recruitment has a crucial role in inflammation and immunity. An interplay between adhesion molecules and pro-adhesive agonists generates a complex molecular network controlling tissue-specific and inflammation-dependent leukocyte vascular recognition. Recent findings highlight the importance of quantitative parameters in controlling the specificity of leukocyte vascular recognition. Introduction of quantitative parameters demonstrates the non-linear behavior of the process and suggests the necessity for a revision of the traditional model. We propose a formalization of the original multi-step model of leukocyte vascular recognition by introducing the notion of concurrency that explains how the quantitative variation of pro-adhesive parameters might control the specificity and the sensitivity of this process. Moreover, we discuss how concurrency, by integrating quantitative parameters, constitutes a central concept for the implementation of a predictive computer modeling of leukocyte vascular recognition

A BioSpi model of lymphocyte-endothelial interactions in inflamed brain venules.

This paper presents a stochastic model of the lymphocyte recruitment in inflammed brain microvessels. The framework used is based on stochastic process algebras for mobile systems. The automatic tool used in the simulation is the BioSpi

Pacific Symposium on Biocomputing 9:521-532(2004) A BIOSPI MODEL OF LYMPHOCYTE-ENDOTHELIAL INTERACTIONS IN INFLAMED BRAIN VENULES

This paper presents a stochastic model of the lymphocyte recruitment in inflammed brain microvessels. The framework used is based on stochastic process algebras for mobile systems. The automatic tool used in the simulation is the BioSpi. We compare our approach with classical hydrodinamical specifications.