TY - GEN
T1 - Multiple sclerosis disease
T2 - 16th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2019
AU - Pernice, Simone
AU - Beccuti, Marco
AU - Romano, Greta
AU - Pennisi, Marzio
AU - Maglione, Alessandro
AU - Cutrupi, Santina
AU - Pappalardo, Francesco
AU - Capra, Lorenzo
AU - Franceschinis, Giuliana
AU - De Pierro, Massimiliano
AU - Balbo, Gianfranco
AU - Cordero, Francesca
AU - Calogero, Raffaele
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2020.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Colored Petri Nets
KW - Computational model
KW - Multiple Sclerosis
UR - https://www.scopus.com/pages/publications/85098256592
U2 - 10.1007/978-3-030-63061-4_26
DO - 10.1007/978-3-030-63061-4_26
M3 - Conference contribution
AN - SCOPUS:85098256592
SN - 9783030630607
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 299
EP - 308
BT - Computational Intelligence Methods for Bioinformatics and Biostatistics - 16th International Meeting, CIBB 2019, Revised Selected Papers
A2 - Cazzaniga, Paolo
A2 - Besozzi, Daniela
A2 - Merelli, Ivan
A2 - Manzoni, Luca
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 4 September 2019 through 6 September 2019
ER -