- Simone Pernice12,
- Marco Beccuti12,
- Greta Romano12,
- Marzio Pennisi13,
- Alessandro Maglione14,
- Santina Cutrupi14,
- Francesco Pappalardo15,
- Lorenzo Capra16,
- Giuliana Franceschinis13,
- Massimiliano De Pierro12,
- Gianfranco Balbo12,
- Francesca Cordero12 &
- …
- Raffaele Calogero17
Part of the book series:Lecture Notes in Computer Science ((LNBI,volume 12313))
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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.
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Authors and Affiliations
Department of Computer Science, University of Turin, Turin, Italy
Simone Pernice, Marco Beccuti, Greta Romano, Massimiliano De Pierro, Gianfranco Balbo & Francesca Cordero
Computer Science Institute, DiSIT, University of Eastern Piedmont, Alessandria, Italy
Marzio Pennisi & Giuliana Franceschinis
Department of Clinical and Biological Sciences, University of Turin, Orbassano, Italy
Alessandro Maglione & Santina Cutrupi
Department of Drug Sciences, University of Catania, Catania, Italy
Francesco Pappalardo
Department of Computer Science, University of Milan, Milan, Italy
Lorenzo Capra
Department of Molecular Biotechnology and Health Sciences, University of Turin, Turin, Italy
Raffaele Calogero
- Simone Pernice
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- Marco Beccuti
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- Marzio Pennisi
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- Alessandro Maglione
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- Francesco Pappalardo
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- Giuliana Franceschinis
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Correspondence toSimone Pernice.
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Editors and Affiliations
University of Bergamo, Bergamo, Italy
Paolo Cazzaniga
University of Milano-Bicocca, Milan, Italy
Daniela Besozzi
National Research Council, Segrate, Italy
Ivan Merelli
Università degli Studi di Trieste, Trieste, Italy
Luca Manzoni
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Pernice, S.et al. (2020). Multiple Sclerosis Disease: A Computational Approach for Investigating Its Drug Interactions. In: Cazzaniga, P., Besozzi, D., Merelli, I., Manzoni, L. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2019. Lecture Notes in Computer Science(), vol 12313. Springer, Cham. https://doi.org/10.1007/978-3-030-63061-4_26
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