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308 results on '"Pennisi, Marzio"'

1. Verification of an agent-based disease model of human mycobacterium tuberculosis infection

Author

Curreli, Cristina, Pappalardo, Francesco, Russo, Giulia, Pennisi, Marzio, Kiagias, Dimitrios, Juarez, Miguel, and Viceconti, Marco

Subjects
Quantitative Biology - Quantitative Methods
Abstract

Agent-Based Models are a powerful class of computational models widely used to simulate complex phenomena in many different application areas. However, one of the most critical aspects, poorly investigated in the literature, regards an important step of the model credibility assessment: solution verification. This study overcomes this limitation by proposing a general verification framework for Agent-Based Models that aims at evaluating the numerical errors associated with the model. A step-by-step procedure, which consists of two main verification studies (deterministic and stochastic model verification), is described in detail and applied to a specific mission critical scenario: the quantification of the numerical approximation error for UISS-TB, an ABM of the human immune system developed to predict the progression of pulmonary tuberculosis. Results provide indications on the possibility to use the proposed model verification workflow to systematically identify and quantify numerical approximation errors associated with UISS-TB and, in general, with any other ABMs.

Published
2021

2. Exploiting Structural Dependency Relations for Efficient Agent Based Model Simulation

Author

Pennisi, Marzio, Amparore, Elvio G., Franceschinis, Giuliana, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Iacono, Mauro, editor, Scarpa, Marco, editor, Barbierato, Enrico, editor, Serrano, Salvatore, editor, Cerotti, Davide, editor, and Longo, Francesco, editor

Published
2023
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3. Multiple Sclerosis disease: a computational approach for investigating its drug interactions

Author

Pernice, Simone, Beccuti, Marco, Romano, Greta, Pennisi, Marzio, Maglione, Alessandro, Cutrupi, Santina, Pappalardo, Francesco, Capra, Lorenzo, Franceschinis, Giuliana, De Pierro, Massimiliano, Balbo, Gianfranco, Cordero, Francesca, and Calogero, Raffaele

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Computational Engineering, Finance, and Science
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 provided, 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. Thus, 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 Daclizumab drug, taking into account also spatiality and temporality of the involved phenomena. Moreover, we show how the intrinsic symmetries of the system can be exploited to drastically reduce the complexity of its analysis., Comment: Submitted to CIBB 2019 post proceedings - LNCS

Published
2020

4. In Silico Trial to test COVID-19 candidate vaccines: a case study with UISS platform

Author

Russo, Giulia, Pennisi, Marzio, Viceconti, Marco, and Pappalardo, Francesco

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Multiagent Systems, Quantitative Biology - Populations and Evolution, Quantitative Biology - Tissues and Organs
Abstract

SARS-CoV-2 is a severe respiratory infection that infects humans. Its outburst entitled it as a pandemic emergence. To get a grip on this, outbreak specific preventive and therapeutic interventions are urgently needed. It must be said that, until now, there are no existing vaccines for coronaviruses. To promptly and rapidly respond to pandemic events, the application of in silico trials can be used for designing and testing medicines against SARS-CoV-2 and speed-up the vaccine discovery pipeline, predicting any therapeutic failure and minimizing undesired effects. Here, we present an in silico platform that showed to be in very good agreement with the latest literature in predicting SARS- CoV-2 dynamics and related immune system host response. Moreover, it has been used to predict the outcome of one of the latest suggested approach to design an effective vaccine, based on monoclonal antibody. UISS is then potentially ready to be used as an in silico trial platform to predict the outcome of vaccination strategy against SARS-CoV-2., Comment: 8 pages, 7 figures

Published
2020

5. Generation of digital patients for the simulation of tuberculosis with UISS-TB

Author

Pennisi, Marzio, Juarez, Miguel A., Russo, Giulia, Viceconti, Marco, and Pappalardo, Francesco

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Multiagent Systems
Abstract

EC funded STriTuVaD project aims to test, through a phase IIb clinical trial, two of the most advanced therapeutic vaccines against tuberculosis. In parallel, we have extended the Universal Immune System Simulator to include all relevant determinants of such clinical trial, to establish its predictive accuracy against the individual patients recruited in the trial, to use it to generate digital patients and predict their response to the HRT being tested, and to combine them to the observations made on physical patients using a new in silico-augmented clinical trial approach that uses a Bayesian adaptive design. This approach, where found effective could drastically reduce the cost of innovation in this critical sector of public healthcare. One of the most challenging task is to develop a methodology to reproduce biological diversity of the subjects that have to be simulated, i.e., provide an appropriate strategy for the generation of libraries of digital patients. This has been achieved through the the creation of the initial immune system repertoire in a stochastic way, and though the identification of a "vector of features" that combines both biological and pathophysiological parameters that personalize the digital patient to reproduce the physiology and the pathophysiology of the subject., Comment: 5 pages

Published
2019

6. Evaluation of the efficacy of RUTI and ID93/GLA-SE vaccines in tuberculosis treatment: in silico trial through UISS-TB simulator

Author

Russo, Giulia, Pappalardo, Francesco, Juarez, Miguel A., Pennisi, Marzio, Cardona, Pere Joan, Coler, Rhea, Fichera, Epifanio, and Viceconti, Marco

Subjects
Quantitative Biology - Quantitative Methods
Abstract

Tuberculosis (TB) is one of the deadliest diseases worldwide, with 1,5 million fatalities every year along with potential devastating effects on society, families and individuals. To address this alarming burden, vaccines can play a fundamental role, even though to date no fully effective TB vaccine really exists. Current treatments involve several combinations of antibiotics administered to TB patients for up to two years, leading often to financial issues and reduced therapy adherence. Along with this, the development and spread of drug-resistant TB strains is another big complicating matter. Faced with these challenges, there is an urgent need to explore new vaccination strategies in order to boost immunity against tuberculosis and shorten the duration of treatment. Computational modeling represents an extraordinary way to simulate and predict the outcome of vaccination strategies, speeding up the arduous process of vaccine pipeline development and relative time to market. Here, we present EU - funded STriTuVaD project computational platform able to predict the artificial immunity induced by RUTI and ID93/GLA-SE, two specific tuberculosis vaccines. Such an in silico trial will be validated through a phase 2b clinical trial. Moreover, STriTuVaD computational framework is able to inform of the reasons for failure should the vaccinations strategies against M. tuberculosis under testing found not efficient, which will suggest possible improvements., Comment: 5 pages

Published
2019

7. Gene expression and pathway bioinformatics analysis detect a potential predictive value of MAP3K8 in thyroid cancer progression

Author

Di Salvatore, Valentina, Gianì, Fiorenza, Russo, Giulia, Pennisi, Marzio, Malandrino, Pasqualino, Frasca, Francesco, and Pappalardo, Francesco

Subjects
Quantitative Biology - Molecular Networks, Computer Science - Other Computer Science
Abstract

Thyroid cancer is the commonest endocrine malignancy. Mutation in the BRAF serine/threonine kinase is the most frequent genetic alteration in thyroid cancer. Target therapy for advanced and poorly differentiated thyroid carcinomas include BRAF pathway inhibitors. Here, we evaluated the role of MAP3K8 expression as a potential driver of resistance to BRAF inhibition in thyroid cancer. By analyzing Gene Expression Omnibus data repository, across all thyroid cancer histotypes, we found that MAP3K8 is up-regulated in poorly differentiated thyroid carcinomas and its expression is related to a stem cell like phenotype and a poorer prognosis and survival. Taken together these data unravel a novel mechanism for thyroid cancer progression and chemo-resistance and confirm previous results obtained in cultured thyroid cancer stem cells, Comment: 5 pages

Published
2019

8. POSITION PAPER: Credibility of In Silico Trial Technologies: A Theoretical Framing

Author

Viceconti, Marco, Juárez, Miguel A., Curreli, Cristina, Pennisi, Marzio, Russo, Giulia, and Pappalardo, Francesco

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Computational Engineering, Finance, and Science
Abstract

Different research communities have developed various approaches to assess the credibility of predictive models. Each approach usually works well for a specific type of model, and under some epistemic conditions that are normally satisfied within that specific research domain. Some regulatory agencies recently started to consider evidences of safety and efficacy on new medical products obtained using computer modelling and simulation (which is referred to as In Silico Trials); this has raised the attention in the computational medicine research community on the regulatory science aspects of this emerging discipline. But this poses a foundational problem: in the domain of biomedical research the use of computer modelling is relatively recent, without a widely accepted epistemic framing for problem of model credibility. Also, because of the inherent complexity of living organisms, biomedical modellers tend to use a variety of modelling methods, sometimes mixing them in the solution of a single problem. In such context merely adopting credibility approaches developed within other research community might not be appropriate. In this position paper we propose a theoretical framing for the problem of assessing the credibility of a predictive models for In Silico Trials, which accounts for the epistemic specificity of this research field and is general enough to be used for different type of models., Comment: 11 pages

Published
2019

10. In Silico Evaluation of Daclizumab and Vitamin D Effects in Multiple Sclerosis Using Agent Based Models

Author

Pennisi, Marzio, Russo, Giulia, Sgroi, Giuseppe, Palumbo, Giuseppe Alessandro Parasiliti, Pappalardo, Francesco, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Cazzaniga, Paolo, editor, Besozzi, Daniela, editor, Merelli, Ivan, editor, and Manzoni, Luca, editor

Published
2020
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11. Efficient and Settings-Free Calibration of Detailed Kinetic Metabolic Models with Enzyme Isoforms Characterization

Author

Totis, Niccolò, Tagherloni, Andrea, Beccuti, Marco, Cazzaniga, Paolo, Nobile, Marco S., Besozzi, Daniela, Pennisi, Marzio, Pappalardo, Francesco, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Raposo, Maria, editor, Ribeiro, Paulo, editor, Sério, Susana, editor, Staiano, Antonino, editor, and Ciaramella, Angelo, editor

Published
2020
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12. GPU Accelerated Analysis of Treg-Teff Cross Regulation in Relapsing-Remitting Multiple Sclerosis

Author

Beccuti, Marco, Cazzaniga, Paolo, Pennisi, Marzio, Besozzi, Daniela, Nobile, Marco S., Pernice, Simone, Russo, Giulia, Tangherloni, Andrea, Pappalardo, Francesco, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Mencagli, Gabriele, editor, B. Heras, Dora, editor, Cardellini, Valeria, editor, Casalicchio, Emiliano, editor, Jeannot, Emmanuel, editor, Wolf, Felix, editor, Salis, Antonio, editor, Schifanella, Claudio, editor, Manumachu, Ravi Reddy, editor, Ricci, Laura, editor, Beccuti, Marco, editor, Antonelli, Laura, editor, Garcia Sanchez, José Daniel, editor, and Scott, Stephen L., editor

Published
2019
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13. OmniReprodubileCellAnalysis: a comprehensive toolbox for the analysis of cellular biology data

Author

Tortarolo, Dora, primary, Pernice, Simone, additional, Clapero, Fabiana, additional, Valdembri, Donatella, additional, Serini, Guido, additional, Riccardo, Federica, additional, Tarone, Lidia, additional, Bena, Chiara Enrico, additional, Bosia, Carla, additional, Contaldo, Sandro Gepiro, additional, Beccuti, Marco, additional, Pennisi, Marzio, additional, and Cordero, Francesca, additional

Published
2023
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16. BIOESOnet: A Tool for the Generation of Personalized Human Metabolic Pathways from 23andMe Exome Data

Author

Pennisi, Marzio, Forzano, Gabriele, Russo, Giulia, Tomasello, Barbara, Favetta, Marco, Renis, Marcella, Pappalardo, Francesco, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Huang, De-Shuang, editor, Jo, Kang-Hyun, editor, and Zhang, Xiao-Long, editor

Published
2018
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21. Multiple Sclerosis Disease: A Computational Approach for Investigating Its Drug Interactions

Author

Pernice, Simone, primary, Beccuti, Marco, additional, Romano, Greta, additional, Pennisi, Marzio, additional, Maglione, Alessandro, additional, Cutrupi, Santina, additional, Pappalardo, Francesco, additional, Capra, Lorenzo, additional, Franceschinis, Giuliana, additional, De Pierro, Massimiliano, additional, Balbo, Gianfranco, additional, Cordero, Francesca, additional, and Calogero, Raffaele, additional

Published
2020
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22. Modeling PI3K/PDK1/Akt and MAPK Signaling Pathways Using Continuous Petri Nets

Author

Russo, Giulia, Pennisi, Marzio, Boscarino, Roberta, Pappalardo, Francesco, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Huang, De-Shuang, editor, Jo, Kang-Hyun, editor, and Figueroa-García, Juan Carlos, editor

Published
2017
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23. 2DIs: A SBML Compliant Web Platform for the Design and Modeling of Immune System Interactions

Author

Pennisi, Marzio, Russo, Giulia, Sgroi, Giuseppe, Parasiliti, Giuseppe, Pappalardo, Francesco, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Huang, De-Shuang, editor, Jo, Kang-Hyun, editor, and Figueroa-García, Juan Carlos, editor

Published
2017
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32. Computational Immunogenetics

Author

Gómez Perosanz, Marta, primary, Russo, Giulia, additional, Sanchez-Trincado Lopez, Jose Luis, additional, Pennisi, Marzio, additional, Reche, Pedro A., additional, Shepherd, Adrian, additional, and Pappalardo, Francesco, additional

Published
2019
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35. OntoFast: Construct Ontology Rapidly

Author

Rajput, Abdul-Mateen, Pennisi, Marzio, Motta, Santo, Pappalardo, Francesco, Junqueira Barbosa, Simone Diniz, Series editor, Chen, Phoebe, Series editor, Cuzzocrea, Alfredo, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kara, Orhun, Series editor, Kotenko, Igor, Series editor, Sivalingam, Krishna M., Series editor, Ślęzak, Dominik, Series editor, Washio, Takashi, Series editor, Yang, Xiaokang, Series editor, Klinov, Pavel, editor, and Mouromtsev, Dmitry, editor

Published
2014
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39. Predicting Long-Term Vaccine Efficacy against Metastases Using Agents

Author

Pennisi, Marzio, Motta, Dario, Cincotti, Alessandro, Pappalardo, Francesco, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Istrail, Sorin, editor, Pevzner, Pavel, editor, Waterman, Michael S., editor, Huang, De-Shuang, editor, Gan, Yong, editor, Premaratne, Prashan, editor, and Han, Kyungsook, editor

Published
2012
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41. GRIDUISS – A Grid Based Universal Immune System Simulator Framework

Author

Pappalardo, Francesco, Pennisi, Marzio, Chiacchio, Ferdinando, Cincotti, Alessandro, Motta, Santo, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Huang, De-Shuang, editor, Zhao, Zhongming, editor, Bevilacqua, Vitoantonio, editor, and Figueroa, Juan Carlos, editor

Published
2010
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42. The ImmunoGrid Simulator: How to Use It

Author

Pappalardo, Francesco, Halling-Brown, Mark, Pennisi, Marzio, Chiacchio, Ferdinando, Sansom, Clare E., Shepherd, Adrian J., Moss, David S., Motta, Santo, Brusic, Vladimir, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Istrail, Sorin, editor, Pevzner, Pavel, editor, Waterman, Michael S., editor, Masulli, Francesco, editor, Peterson, Leif E., editor, and Tagliaferri, Roberto, editor

Published
2010
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43. Agent Based Modeling of Atherosclerosis: A Concrete Help in Personalized Treatments

Author

Pappalardo, Francesco, Cincotti, Alessandro, Motta, Alfredo, Pennisi, Marzio, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Huang, De-Shuang, editor, Jo, Kang-Hyun, editor, Lee, Hong-Hee, editor, Kang, Hee-Jun, editor, and Bevilacqua, Vitoantonio, editor

Published
2009
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49. Agent Based Modeling of Lung Metastasis-Immune System Competition

Author

Pennisi, Marzio, Pappalardo, Francesco, Motta, Santo, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Andrews, Paul S., editor, Timmis, Jon, editor, Owens, Nick D. L., editor, Aickelin, Uwe, editor, Hart, Emma, editor, Hone, Andrew, editor, and Tyrrell, Andy M., editor

Published
2009
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50. ImmunoGrid: towards agent-based simulations of the human immune system at a natural scale

Author

Halling-Brown, Mark, Pappalardo, Francesco, Rapin, Nicolas, Zhang, Ping, Alemani, Davide, Emerson, Andrew, Castiglione, Filippo, Duroux, Patrice, Pennisi, Marzio, Miotto, Olivo, Churchill, Daniel, Rossi, Elda, Moss, David S., Sansom, Clare E., Bernaschi, Massimo, Lefranc, Marie-Paule, Brunak, Søren, Lund, Ole, Motta, Santo, Lollini, Pier-Luigi, Murgo, Annalisa, Palladini, Arianna, Basford, Kaye E., Brusic, Vladimir, and Shepherd, Adrian J.

Published
2010

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