Large scale agent-based modeling of the humoral and cellular immune response

Neurology and Centre for Experimental Neurological Therapies (CENTERS), S. Andrea Hospital Site, Sapienza University of Rome, 00189, Roma, Italy
LNCS 01/2011; 6825:15-29. DOI: 10.1007/978-3-642-22371-6_2
Source: DBLP


The Immune System is, together with Central Nervous System, one of the most important and complex unit of our organism. Despite great advances in recent years that shed light on its understand-ing and in the unraveling of key mechanisms behind its functions, there are still many areas of the Immune System that remain object of ac-tive research. The development of in-silico models, bridged with proper biological considerations, have recently improved the understanding of important complex systems [1,2]. In this paper, after introducing major role players and principal functions of the mammalian Immune System, we present two computational approaches to its modeling; i.e., two in-silico Immune Systems. (i) A large-scale model, with a complexity of representation of 10 6 − 10 8 cells (e.g., APC, T, B and Plasma cells) and molecules (e.g., immunocomplexes), is here presented, and its evolution in time is shown to be mimicking an important region of a real im-mune response. (ii) Additionally, a viral infection model, stochastic and light-weight, is here presented as well: its seamless design from biological considerations, its modularity and its fast simulation times are strength points when compared to (i). Finally we report, with the intent of mov-ing towards the virtual lymph note, a cost-benefits comparison among Immune System models presented in this paper.

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