Francesco Pappalardo 0001 - researchr alias

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Viewing Publication 1 - 57 from 57

2023

2022

Genetic algorithm application for the prediction of potential SARS-CoV-2 new variant of concernAvisa Maleki, Alvaro Ras-Carmona, Valentina Di Salvatore, Giulia Russo, Elena Crispino, Francesco Pappalardo 0001. bibm 2022: 3549-3551 [doi]

Cutaneous Leishmaniasis: discovering new effective therapies using the Universal Immune System SimulatorNandu Chandran Nair, Elena Crispino, Avisa Maleki, Valentina Di Salvatore, Giulia Russo, Maria Adelaida Gomez, Francesco Pappalardo 0001. bibm 2022: 3552-3555 [doi]

UISS-GPU: Accelerated In-Silico Tuberculosis Vaccine Trials Using FLAME GPUPaul Richmond, Matthew Leach, Peter Heywood, Francesco Pappalardo 0001, Giulia Russo, Marzio Pennisi. bibm 2022: 3562-3568 [doi]

A multi-step and multi-scale bioinformatic protocol to investigate potential SARS-CoV-2 vaccine targetsGiulia Russo, Valentina Di Salvatore, Giuseppe Sgroi, Giuseppe Alessandro Parasiliti Palumbo, Pedro A. Reche, Francesco Pappalardo 0001. bib, 23(1), 2022. [doi]

In silico clinical trials for relapsing-remitting multiple sclerosis with MS TreatSimFianne L. P. Sips, Francesco Pappalardo 0001, Giulia Russo, Roberta Bursi. midm, 22-S(6):294, 2022. [doi]

2021

How molecular packets improve cell-to-cell communicationFrancesco Pappalardo 0001, N. Iraci, L. Leggio, Alessandro Lombardo, Giacomo Morabito. nanocom 2021: [doi]

In silico design of recombinant multi-epitope vaccine against influenza A virusAvisa Maleki, Giulia Russo, Giuseppe Alessandro Parasiliti Palumbo, Francesco Pappalardo 0001. bmcbi, 22-S(14):617, 2021. [doi]

Uncertainty quantification and sensitivity analysis for in silico trial platform: a preliminary application on UISS-MSGiuseppe Alessandro Parasiliti Palumbo, Avisa Maleki, Serena Anna Italia, Giulia Russo, Francesco Pappalardo 0001. bibm 2021: 3299-3302 [doi]

Model verification tools: a computational framework for verification assessment of mechanistic agent-based modelsGiulia Russo, Giuseppe Alessandro Parasiliti Palumbo, Marzio Pennisi, Francesco Pappalardo 0001. bmcbi, 22-S(14):626, 2021. [doi]

A multi-step and multi-scale bioinformatic approach to investigate potential source of cross-reactive immunity against SARS-CoV-2 UK variantValentina Di Salvatore, Avisa Maleki, Giulia Russo, Giuseppe Sgroi, Giuseppe Alessandro Parasiliti Palumbo, Francesco Pappalardo 0001. bibm 2021: 3303-3307 [doi]

PEAK: A Clever Python Tool for Exploratory, Regression, and Classification Data. A Case Study for COVID-19Giuseppe Sgroi, Giuseppe Alessandro Parasiliti Palumbo, Valentina Di Salvatore, Giulia Russo, Francesco Pappalardo 0001. biomesip 2021: 361-370 [doi]

Evaluation of word embedding models to extract and predict surgical data in breast cancerGiuseppe Sgroi, Giulia Russo, Anna Maglia, Giuseppe Catanuto, Peter Barry, Andreas Karakatsanis, Nicola Rocco, Francesco Pappalardo 0001. bmcbi, 22-S(14):631, 2021. [doi]

PETAL: a Python tool for deep analysis of biological pathwaysGiuseppe Sgroi, Giulia Russo, Francesco Pappalardo 0001. bioinformatics, 36(22-23):5553-5555, 2021. [doi]

2020

Toward computational modelling on immune system functionFrancesco Pappalardo 0001, Giulia Russo, Pedro A. Reche. bmcbi, 21-S(17):546, 2020. [doi]

Generation of digital patients for the simulation of tuberculosis with UISS-TBMiguel A. Juárez, Marzio Pennisi, Giulia Russo, Dimitrios Kiagias, Cristina Curreli, Marco Viceconti, Francesco Pappalardo 0001. bmcbi, 21-S(17):449, 2020. [doi]

Verify: a toolbox for deterministic verification of computational modelsGiuseppe Alessandro Parasiliti Palumbo, Giulia Russo, Giuseppe Sgroi, Marco Viceconti, Marzio Pennisi, Cristina Curreli, Francesco Pappalardo 0001. bibm 2020: 1262-1267 [doi]

Computational modeling of the immune response in multiple sclerosis using epimod frameworkSimone Pernice, Laura Follia, Alessandro Maglione, Marzio Pennisi, Francesco Pappalardo 0001, Francesco Novelli, Marinella Clerico, Marco Beccuti, Francesca Cordero, Simona Rolla. bmcbi, 21-S(17):550, 2020. [doi]

Moving forward through the in silico modeling of tuberculosis: a further step with UISS-TBGiulia Russo, Giuseppe Sgroi, Giuseppe Alessandro Parasiliti Palumbo, Marzio Pennisi, Miguel A. Juárez, Pere Joan Cardona, Santo Motta, Kenneth B. Walker, Epifanio Fichera, Marco Viceconti, Francesco Pappalardo 0001. bmcbi, 21-S(17):458, 2020. [doi]

In silico trial to test COVID-19 candidate vaccines: a case study with UISS platformGiulia Russo, Marzio Pennisi, Epifanio Fichera, Santo Motta, Giuseppina Raciti, Marco Viceconti, Francesco Pappalardo 0001. bmcbi, 21-S(17):527, 2020. [doi]

Modeling, simulation and prediction of protein structures for the design of oncolytic virusesValentina Di Salvatore, Daniela Formica, Giulia Russo, Viviana Giannino, Francesco Pappalardo 0001. bibm 2020: 1268-1274 [doi]

Evaluation of the predictive capability of PETAL tool: a retrospective study on potential tyrosine kinases drug resistance targetsGiuseppe Sgroi, Marzio Pennisi, Giulia Russo, Francesco Pappalardo 0001, Giuseppe Alessandro Parasiliti Palumbo. bibm 2020: 1275-1280 [doi]

Credibility of In Silico Trial Technologies - A Theoretical FramingMarco Viceconti, Miguel A. Juárez, Cristina Curreli, Marzio Pennisi, Giulia Russo, Francesco Pappalardo 0001. titb, 24(1):4-13, 2020. [doi]

2019

Toward computational modelling on immune system functionFrancesco Pappalardo 0001, Marzio Pennisi, Pedro A. Reche, Giulia Russo. bmcbi, 20-S(6):622, December 2019. [doi]

In silico clinical trials: concepts and early adoptionsFrancesco Pappalardo 0001, Giulia Russo, Flora Musuamba Tshinanu, Marco Viceconti. bib, 20(5):1699-1708, 2019. [doi]

EpiMethEx: a tool for large-scale integrated analysis in methylation hotspots linked to genetic regulationSaverio Candido, Giuseppe Alessandro Parasiliti Palumbo, Marzio Pennisi, Giulia Russo, Giuseppe Sgroi, Valentina Di Salvatore, Massimo Libra, Francesco Pappalardo 0001. bmcbi, 19(13):43-53, 2019. [doi]

Parallelisation strategies for agent based simulation of immune systemsMozhgan Kabiri Chimeh, Peter Heywood, Marzio Pennisi, Francesco Pappalardo 0001, Paul Richmond. bmcbi, 20-S(6):579, 2019. [doi]

Computational modeling reveals MAP3K8 as mediator of resistance to vemurafenib in thyroid cancer stem cellsFiorenza Gianì, Giulia Russo, Marzio Pennisi, Laura Sciacca, Francesco Frasca, Francesco Pappalardo 0001. bioinformatics, 35(13):2267-2275, 2019. [doi]

A MapReduce tool for in-depth analysis of KEGG pathways: identification and visualization of therapeutic target candidatesGiuseppe Alessandro Parasiliti Palumbo, Pietro Biondi, Giuseppe Sgroi, Marzio Pennisi, Giulia Russo, Francesco Pappalardo 0001. bibm 2019: 2157-2162 [doi]

A MapReduce Based Tool for the Analysis and Discovery of Novel Therapeutic TargetsGiuseppe Parasiliti, Marzio Pennisi, Pietro Biondi, Giuseppe Sgroi, Giulia Russo, Christian Napoli, Francesco Pappalardo 0001. pdp 2019: 323-328 [doi]

In Silico Evaluation of Daclizumab and Vitamin D Effects in Multiple Sclerosis Using Agent Based ModelsMarzio Pennisi, Giulia Russo, Giuseppe Sgroi, Giuseppe Alessandro Parasiliti Palumbo, Francesco Pappalardo 0001. cibb 2020: 285-298 [doi]

Generation of digital patients for the simulation of tuberculosis with UISS-TBMarzio Pennisi, Miguel A. Juárez, Giulia Russo, Marco Viceconti, Francesco Pappalardo 0001. bibm 2019: 2163-2167 [doi]

Predicting the artificial immunity induced by RUTI® vaccine against tuberculosis using universal immune system simulator (UISS)Marzio Pennisi, Giulia Russo, Giuseppe Sgroi, Angela Bonaccorso, Giuseppe Alessandro Parasiliti Palumbo, Epifanio Fichera, Dipendra Kumar Mitra, Kenneth B. Walker, Pere Joan Cardona, Merce Amat, Marco Viceconti, Francesco Pappalardo 0001. bmcbi, 20-S(6):504, 2019. [doi]

A computational approach based on the colored Petri net formalism for studying multiple sclerosisSimone Pernice, Marzio Pennisi, Greta Romano, Alessandro Maglione, Santina Cutrupi, Francesco Pappalardo 0001, Gianfranco Balbo, Marco Beccuti, Francesca Cordero, Raffaele A. Calogero. bmcbi, 20-S(6):623, December 2019. [doi]

Multiple Sclerosis Disease: A Computational Approach for Investigating Its Drug InteractionsSimone Pernice, Marco Beccuti, Greta Romano, Marzio Pennisi, Alessandro Maglione, Santina Cutrupi, Francesco Pappalardo 0001, Lorenzo Capra, Giuliana Franceschinis, Massimiliano De Pierro, Gianfranco Balbo, Francesca Cordero, Raffaele A. Calogero. cibb 2020: 299-308 [doi]

Exploiting Stochastic Petri Net formalism to capture the Relapsing Remitting Multiple Sclerosis variability under Daclizumab administrationSimone Pernice, Greta Romano, Giulia Russo, Marco Beccuti, Marzio Pennisi, Francesco Pappalardo 0001. bibm 2019: 2168-2175 [doi]

Evaluation of the efficacy of RUTI and ID93/GLA-SE vaccines in tuberculosis treatment: in silico trial through UISS-TB simulatorGiulia Russo, Francesco Pappalardo 0001, Miguel A. Juárez, Marzio Pennisi, Pere Joan Cardona, Rhea Coler, Epifanio Fichera, Marco Viceconti. bibm 2019: 2197-2201 [doi]

Gene expression and pathway bioinformatics analysis detect a potential predictive value of MAP3K8 in thyroid cancer progressionValentina Di Salvatore, Fiorenza Gianì, Giulia Russo, Marzio Pennisi, Pasqualino Malandrino, Francesco Frasca, Francesco Pappalardo 0001. bibm 2019: 2202-2206 [doi]

2018

An agent based modeling approach for the analysis of tuberculosis - immune system dynamicsFrancesco Pappalardo 0001, Giulia Russo, Marzio Pennisi, Giuseppe Sgroi, Giuseppe Alessandro, Parasiliti Palumbo, Santo Motta, Epifanio Fichera. bibm 2018: 1386-1392 [doi]

Agent based modeling of relapsing multiple sclerosis: a possible approach to predict treatment outcomeFrancesco Pappalardo 0001, Giulia Russo, Marzio Pennisi, Giuseppe Sgroi, Giuseppe Alessandro, Parasiliti Palumbo, Santo Motta, Davide Maimone, Ferdinando Chiacchio. bibm 2018: 1380-1385 [doi]

Computational modeling of brain pathologies: the case of multiple sclerosisFrancesco Pappalardo 0001, Abdul Mateen Rajput, Santo Motta. bib, 19(2):318-324, 2018. [doi]

GPU Accelerated Analysis of Treg-Teff Cross Regulation in Relapsing-Remitting Multiple SclerosisMarco Beccuti, Paolo Cazzaniga, Marzio Pennisi, Daniela Besozzi, Marco S. Nobile, Simone Pernice, Giulia Russo, Andrea Tangherloni, Francesco Pappalardo 0001. europar 2019: 626-637 [doi]

Parallel Pair-Wise Interaction for Multi-Agent Immune Systems ModellingMozhgan K. Chimeh, Peter Heywood, Marzio Pennisi, Francesco Pappalardo 0001, Paul Richmond. bibm 2018: 1367-1373 [doi]

Combining Parallel Genetic Algorithms and Machine Learning to Improve the Research of Optimal Vaccination ProtocolsMarzio Pennisi, Giulia Russo, Francesco Pappalardo 0001. pdp 2018: 399-405 [doi]

BIOESOnet: A Tool for the Generation of Personalized Human Metabolic Pathways from 23andMe Exome DataMarzio Pennisi, Gabriele Forzano, Giulia Russo, Barbara Tomasello, Marco Favetta, Marcella Renis, Francesco Pappalardo 0001. icic 2018: 345-352 [doi]

Estimating Daclizumab effects in Multiple Sclerosis using Stochastic Symmetric NetsSimone Pernice, Marco Beccuti, Pietro Do', Marzio Pennisi, Francesco Pappalardo 0001. bibm 2018: 1393-1400 [doi]

Continuous Petri Nets and microRNA Analysis in MelanomaGiulia Russo, Marzio Pennisi, Roberta Boscarino, Francesco Pappalardo 0001. tcbb, 15(5):1492-1499, 2018. [doi]

Efficient and Settings-Free Calibration of Detailed Kinetic Metabolic Models with Enzyme Isoforms CharacterizationNiccoló Totis, Andrea Tangherloni, Marco Beccuti, Paolo Cazzaniga, Marco S. Nobile, Daniela Besozzi, Marzio Pennisi, Francesco Pappalardo 0001. cibb 2020: 187-202 [doi]

2017

2004

Algoritmi evolutivi per l'approssimazione di problemi di ottimizzazione combinatoricaFrancesco Pappalardo 0001. PhD thesis, University of Catania, Italy, 2004. [doi]

2002

An evolutionary algorithm for the T-constrained variation of Minimum Hitting Set problemVincenzo Cutello, Emilio Mastriani, Francesco Pappalardo 0001. cec 2002: 366-371 [doi]

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