Exploiting Stochastic Petri Net formalism to capture the Relapsing Remitting Multiple Sclerosis variability under Daclizumab administration
暂无分享,去创建一个
Marco Beccuti | Giulia Russo | Francesco Pappalardo | Simone Pernice | Marzio Pennisi | Greta Romano | F. Pappalardo | M. Pennisi | G. Russo | M. Beccuti | S. Pernice | G. Romano
[1] Milanesi Luciano,et al. Integrating Petri Nets and Flux Balance Methods in Computational Biology Models : a Methodological and Computational Practice , 2019 .
[2] John Lygeros,et al. Stochastic Hybrid Models: An Overview , 2003, ADHS.
[3] D. Gillespie. Approximate accelerated stochastic simulation of chemically reacting systems , 2001 .
[4] J. Rawlings,et al. Approximate simulation of coupled fast and slow reactions for stochastic chemical kinetics , 2002 .
[5] Marco Beccuti,et al. Integrating Petri Nets and Flux Balance Methods in Computational Biology Models: a Methodological and Computational Practice , 2020, Fundam. Informaticae.
[6] Abdul Mateen Rajput,et al. Agent based modeling of Treg-Teff cross regulation in relapsing-remitting multiple sclerosis , 2013, BMC Bioinformatics.
[7] Marco Beccuti,et al. GPU Accelerated Analysis of Treg-Teff Cross Regulation in Relapsing-Remitting Multiple Sclerosis , 2018, Euro-Par Workshops.
[8] Hong Li,et al. Efficient formulation of the stochastic simulation algorithm for chemically reacting systems. , 2004, The Journal of chemical physics.
[9] Francesco Pappalardo,et al. Agent based modeling of the effects of potential treatments over the blood-brain barrier in multiple sclerosis. , 2015, Journal of immunological methods.
[10] Michael A. Gibson,et al. Efficient Exact Stochastic Simulation of Chemical Systems with Many Species and Many Channels , 2000 .
[11] Marco Beccuti,et al. GreatSPN Enhanced with Decision Diagram Data Structures , 2010, Petri Nets.
[12] Joaquín Goñi,et al. Modeling the effector - regulatory T cell cross-regulation reveals the intrinsic character of relapses in Multiple Sclerosis , 2011, BMC Systems Biology.
[13] Ferdinando Chiacchio,et al. Relapsing-remitting multiple scleroris and the role of vitamin D: an agent based model , 2014, BCB.
[14] D. Gillespie. Exact Stochastic Simulation of Coupled Chemical Reactions , 1977 .
[15] Marco Beccuti,et al. A computational approach based on the colored Petri net formalism for studying multiple sclerosis , 2019, BMC Bioinformatics.
[16] Matt Shirley,et al. Daclizumab: A Review in Relapsing Multiple Sclerosis , 2017, Drugs.
[17] Xiaoli Yu,et al. Viruses and multiple sclerosis. , 2011, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.
[18] B. Trapp,et al. Mechanisms of neuronal dysfunction and degeneration in multiple sclerosis , 2011, Progress in neurobiology.
[19] Marco Ajmone Marsan,et al. Modelling with Generalized Stochastic Petri Nets , 1995, PERV.
[20] Beccuti Marco,et al. Estimating Daclizumab effects in Multiple Sclerosis using Stochastic Symmetric Nets , 2018, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).