Sfoglia per Autore
Credibility of In Silico Trial Technologies - A Theoretical Framing
2020-01-01 Viceconti, Marco; Juarez, Miguel; Curreli, Cristina; Pennisi, Marzio; Russo, Giulia; Pappalardo, Francesco
Gene Silencing of Transferrin-1 Receptor as a Potential Therapeutic Target for Human Follicular and Anaplastic Thyroid Cancer
2020-01-01 Campisi, A.; Bonfanti, R.; Raciti, G.; Bonaventura, G.; Legnani, L.; Magro, G.; Pennisi, M.; Russo, Giulia.; Chiacchio, M. A.; Pappalardo, F.; Parenti, R.
Moving forward through the in silico modeling of tuberculosis: a further step with UISS-TB
2020-01-01 Russo, G.; Sgroi, G.; Parasiliti Palumbo, G. A.; Pennisi, M.; Juarez, M. A.; Cardona, P. -J.; Motta, S.; Walker, K. B.; Fichera, E.; Viceconti, M.; Pappalardo, F.
Toward computational modelling on immune system function
2020-01-01 Pappalardo, F.; Russo, G.; Reche, P. A.
PETAL: A Python tool for deep analysis of biological pathways
2020-01-01 Sgroi, G.; Russo, G.; Pappalardo, F.
The combination of artificial intelligence and systems biology for intelligent vaccine design
2020-01-01 Russo, G.; Reche, P.; Pennisi, M.; Pappalardo, F.
Verify: A toolbox for deterministic verification of computational models
file da validare2020-01-01 Palumbo, G. A. P.; Russo, G.; Sgroi, G.; Viceconti, M.; Pennisi, M.; Curreli, C.; Pappalardo, F.
The Potential of Computational Modeling to Predict Disease Course and Treatment Response in Patients with Relapsing Multiple Sclerosis
2020-01-01 Pappalardo, Francesco; Russo, Giulia; Pennisi, Marzio; Parasiliti Palumbo, Giuseppe Alessandro; Sgroi, Giuseppe; Motta, Santo; Maimone, Davide
Computational modeling of immunologic response to immune checkpoint inhibitors in COVID-19 patients with and without cancer
file da validare2020-01-01 Russo, Giulia; Falzone, Luca; Cacopardo, Bruno Santi; Nunnari, Giuseppe; Francesco, Torino; Scandurra, Giuseppa; Stefani, Stefania; Pappalardo, Francesco; Libra, Massimo
Modeling, simulation and prediction of protein structures for the design of oncolytic viruses
file da validare2020-01-01 Di Salvatore, V.; Formica, D.; Russo, G.; Giannino, V.; Pappalardo, F.
In silico evaluation of daclizumab and vitamin D effects in multiple sclerosis using agent based models
file da validare2020-01-01 Pennisi, M.; Russo, G.; Sgroi, G.; Palumbo, G. A. P.; Pappalardo, F.
Immune-checkpoint inhibitors from cancer to COVID‑19: A promising avenue for the treatment of patients with COVID‑19 (Review)
2021-01-01 Vivarelli, Silvia; Falzone, Luca; Torino, Francesco; Scandurra, Giuseppa; Russo, Giulia; Bordonaro, Roberto; Pappalardo, Francesco; Spandidos, Demetrios; Raciti, Giuseppina; Libra, Massimo
Computational models to predict disease course and treatment response in multiple sclerosis
file da validare2021-01-01 Russo, Giulia; Parasiliti Palumbo, Giuseppe Alessandro; Salvatore, Valentina Di; Maimone, Davide; Pappalardo, Francesco
Possible Contexts of Use for In Silico trials methodologies: a consensus- based review
2021-01-01 Viceconti, Marco; Emili, Luca; Afshari, Payman; Courcelles, Eulalie; Curreli, Cristina; Famaey, Nele; Geris, Liesbet; Horner, Marc; Jori, Maria Cristina; Kulesza, Alexander; Loewe, Axel; Neidlin, Michael; Reiterer, Markus; Rousseau, Cecile F; Russo, Giulia; Sonntag, Simon J; Voisin, Emmanuelle M; Pappalardo, Francesco
Scientific and regulatory evaluation of mechanistic in silico drug and disease models in drug development: Building model credibility
2021-01-01 Musuamba, Flora T; Skottheim Rusten, Ine; Lesage, Raphaëlle; Russo, Giulia; Bursi, Roberta; Emili, Luca; Wangorsch, Gaby; Manolis, Efthymios; Karlsson, Kristin E; Kulesza, Alexander; Courcelles, Eulalie; Boissel, Jean-Pierre; Rousseau, Cécile F; Voisin, Emmanuelle M; Alessandrello, Rossana; Curado, Nuno; Dall'Ara, Enrico; Rodriguez, Blanca; Pappalardo, Francesco; Geris, Liesbet
Verification of an agent-based disease model of human Mycobacterium tuberculosis infection
2021-01-01 Curreli, C.; Pappalardo, F.; Russo, G.; Pennisi, M.; Kiagias, D.; Juarez, M.; Viceconti, M.
Quality by design tools reducing the gap from bench to bedside for nanomedicine
2021-01-01 Bonaccorso, A.; Russo, G.; Pappalardo, F.; Carbone, C.; Puglisi, G.; Pignatello, R.; Musumeci, T.
Model verification tools: a computational framework for verification assessment of mechanistic agent-based models
2021-01-01 Russo, Giulia; Parasiliti Palumbo, Giuseppe Alessandro; Pennisi, Marzio; Pappalardo, Francesco
A multi-step and multi-scale bioinformatic approach to investigate potential source of cross-reactive immunity against SARS-CoV-2 UK variant
file da validare2021-01-01 Salvatore, V. D.; Maleki, A.; Russo, G.; Sgroi, G.; Palumbo, G. A. P.; Pappalardo, F.
Uncertainty quantification and sensitivity analysis for in silico trial platform: A preliminary application on UISS-MS
file da validare2021-01-01 Palumbo, G. A. P.; Maleki, A.; Italia, S. A.; Russo, G.; Pappalardo, F.
| Titolo | Data di pubblicazione | Autore(i) | File |
|---|---|---|---|
| Credibility of In Silico Trial Technologies - A Theoretical Framing | 1-gen-2020 | Viceconti, Marco; Juarez, Miguel; Curreli, Cristina; Pennisi, Marzio; Russo, Giulia; Pappalardo, Francesco | |
| Gene Silencing of Transferrin-1 Receptor as a Potential Therapeutic Target for Human Follicular and Anaplastic Thyroid Cancer | 1-gen-2020 | Campisi, A.; Bonfanti, R.; Raciti, G.; Bonaventura, G.; Legnani, L.; Magro, G.; Pennisi, M.; Russo, Giulia.; Chiacchio, M. A.; Pappalardo, F.; Parenti, R. | |
| Moving forward through the in silico modeling of tuberculosis: a further step with UISS-TB | 1-gen-2020 | Russo, G.; Sgroi, G.; Parasiliti Palumbo, G. A.; Pennisi, M.; Juarez, M. A.; Cardona, P. -J.; Motta, S.; Walker, K. B.; Fichera, E.; Viceconti, M.; Pappalardo, F. | |
| Toward computational modelling on immune system function | 1-gen-2020 | Pappalardo, F.; Russo, G.; Reche, P. A. | |
| PETAL: A Python tool for deep analysis of biological pathways | 1-gen-2020 | Sgroi, G.; Russo, G.; Pappalardo, F. | |
| The combination of artificial intelligence and systems biology for intelligent vaccine design | 1-gen-2020 | Russo, G.; Reche, P.; Pennisi, M.; Pappalardo, F. | |
| Verify: A toolbox for deterministic verification of computational models | 1-gen-2020 | Palumbo, G. A. P.; Russo, G.; Sgroi, G.; Viceconti, M.; Pennisi, M.; Curreli, C.; Pappalardo, F. | file da validare |
| The Potential of Computational Modeling to Predict Disease Course and Treatment Response in Patients with Relapsing Multiple Sclerosis | 1-gen-2020 | Pappalardo, Francesco; Russo, Giulia; Pennisi, Marzio; Parasiliti Palumbo, Giuseppe Alessandro; Sgroi, Giuseppe; Motta, Santo; Maimone, Davide | |
| Computational modeling of immunologic response to immune checkpoint inhibitors in COVID-19 patients with and without cancer | 1-gen-2020 | Russo, Giulia; Falzone, Luca; Cacopardo, Bruno Santi; Nunnari, Giuseppe; Francesco, Torino; Scandurra, Giuseppa; Stefani, Stefania; Pappalardo, Francesco; Libra, Massimo | file da validare |
| Modeling, simulation and prediction of protein structures for the design of oncolytic viruses | 1-gen-2020 | Di Salvatore, V.; Formica, D.; Russo, G.; Giannino, V.; Pappalardo, F. | file da validare |
| In silico evaluation of daclizumab and vitamin D effects in multiple sclerosis using agent based models | 1-gen-2020 | Pennisi, M.; Russo, G.; Sgroi, G.; Palumbo, G. A. P.; Pappalardo, F. | file da validare |
| Immune-checkpoint inhibitors from cancer to COVID‑19: A promising avenue for the treatment of patients with COVID‑19 (Review) | 1-gen-2021 | Vivarelli, Silvia; Falzone, Luca; Torino, Francesco; Scandurra, Giuseppa; Russo, Giulia; Bordonaro, Roberto; Pappalardo, Francesco; Spandidos, Demetrios; Raciti, Giuseppina; Libra, Massimo | |
| Computational models to predict disease course and treatment response in multiple sclerosis | 1-gen-2021 | Russo, Giulia; Parasiliti Palumbo, Giuseppe Alessandro; Salvatore, Valentina Di; Maimone, Davide; Pappalardo, Francesco | file da validare |
| Possible Contexts of Use for In Silico trials methodologies: a consensus- based review | 1-gen-2021 | Viceconti, Marco; Emili, Luca; Afshari, Payman; Courcelles, Eulalie; Curreli, Cristina; Famaey, Nele; Geris, Liesbet; Horner, Marc; Jori, Maria Cristina; Kulesza, Alexander; Loewe, Axel; Neidlin, Michael; Reiterer, Markus; Rousseau, Cecile F; Russo, Giulia; Sonntag, Simon J; Voisin, Emmanuelle M; Pappalardo, Francesco | |
| Scientific and regulatory evaluation of mechanistic in silico drug and disease models in drug development: Building model credibility | 1-gen-2021 | Musuamba, Flora T; Skottheim Rusten, Ine; Lesage, Raphaëlle; Russo, Giulia; Bursi, Roberta; Emili, Luca; Wangorsch, Gaby; Manolis, Efthymios; Karlsson, Kristin E; Kulesza, Alexander; Courcelles, Eulalie; Boissel, Jean-Pierre; Rousseau, Cécile F; Voisin, Emmanuelle M; Alessandrello, Rossana; Curado, Nuno; Dall'Ara, Enrico; Rodriguez, Blanca; Pappalardo, Francesco; Geris, Liesbet | |
| Verification of an agent-based disease model of human Mycobacterium tuberculosis infection | 1-gen-2021 | Curreli, C.; Pappalardo, F.; Russo, G.; Pennisi, M.; Kiagias, D.; Juarez, M.; Viceconti, M. | |
| Quality by design tools reducing the gap from bench to bedside for nanomedicine | 1-gen-2021 | Bonaccorso, A.; Russo, G.; Pappalardo, F.; Carbone, C.; Puglisi, G.; Pignatello, R.; Musumeci, T. | |
| Model verification tools: a computational framework for verification assessment of mechanistic agent-based models | 1-gen-2021 | Russo, Giulia; Parasiliti Palumbo, Giuseppe Alessandro; Pennisi, Marzio; Pappalardo, Francesco | |
| A multi-step and multi-scale bioinformatic approach to investigate potential source of cross-reactive immunity against SARS-CoV-2 UK variant | 1-gen-2021 | Salvatore, V. D.; Maleki, A.; Russo, G.; Sgroi, G.; Palumbo, G. A. P.; Pappalardo, F. | file da validare |
| Uncertainty quantification and sensitivity analysis for in silico trial platform: A preliminary application on UISS-MS | 1-gen-2021 | Palumbo, G. A. P.; Maleki, A.; Italia, S. A.; Russo, G.; Pappalardo, F. | file da validare |
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