Multiple sclerosis disease: A computational approach for investigating its drug interactions
Contributo in Atti di convegno
Data di Pubblicazione:
2020
Abstract:
Multiple Sclerosis (MS) is a chronic and potentially highly disabling disease that can cause permanent damage and deterioration of the central nervous system. In Europe it is the leading cause of non-traumatic disabilities in young adults, since more than 700,000 EU people suffer from MS. Although recent studies on MS pathophysiology have been performed, providing interesting results, MS remains a challenging disease. In this context, thanks to recent advances in software and hardware technologies, computational models and computer simulations are becoming appealing research tools to support scientists in the study of such disease. Motivated by this consideration, we propose in this paper a new model to study the evolution of MS in silico, and the effects of the administration of the daclizumab drug, taking into account also spatiality and temporality of the involved phenomena. Moreover, we show how the intrinsic symmetries of the model we have developed can be exploited to drastically reduce the complexity of its analysis.
Tipologia CRIS:
04A-Conference paper in volume
Keywords:
Colored Petri Nets; Computational model; Multiple Sclerosis
Elenco autori:
Pernice S.; Beccuti M.; Romano G.; Pennisi M.; Maglione A.; Cutrupi S.; Pappalardo F.; Capra L.; Franceschinis G.; De Pierro M.; Balbo G.; Cordero F.; Calogero R.
Link alla scheda completa:
Titolo del libro:
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pubblicato in: