Pennisi M - Search Results

1

Computational modelling approaches to vaccinology.

Pappalardo F, Flower D, Russo G, Pennisi M, Motta S. Pappalardo F, et al. Among authors: pennisi m. Pharmacol Res. 2015 Feb;92:40-5. doi: 10.1016/j.phrs.2014.08.006. Epub 2014 Sep 16. Pharmacol Res. 2015. PMID: 25224605 Review.

2

Searching of optimal vaccination schedules: application of genetic algorithms to approach the problem in cancer immunoprevention.

Pennisi MA, Pappalardo F, Zhang P, Motta S. Pennisi MA, et al. IEEE Eng Med Biol Mag. 2009 Jul-Aug;28(4):67-72. doi: 10.1109/MEMB.2009.932919. IEEE Eng Med Biol Mag. 2009. PMID: 19622427 No abstract available.

3

Advances in Computational Immunology.

Pappalardo F, Brusic V, Pennisi M, Zhang G. Pappalardo F, et al. Among authors: pennisi m. J Immunol Res. 2015;2015:170920. doi: 10.1155/2015/170920. Epub 2015 Dec 30. J Immunol Res. 2015. PMID: 26844232 Free PMC article. No abstract available.

4

Computational modeling in melanoma for novel drug discovery.

Pennisi M, Russo G, Di Salvatore V, Candido S, Libra M, Pappalardo F. Pennisi M, et al. Expert Opin Drug Discov. 2016 Jun;11(6):609-21. doi: 10.1080/17460441.2016.1174688. Epub 2016 Apr 21. Expert Opin Drug Discov. 2016. PMID: 27046143 Review.

5

Agent based simulations in disease modeling Comment on "Towards a unified approach in the modeling of fibrosis: A review with research perspectives" by Martine Ben Amar and Carlo Bianca.

Pappalardo F, Pennisi M. Pappalardo F, et al. Among authors: pennisi m. Phys Life Rev. 2016 Jul;17:110-1. doi: 10.1016/j.plrev.2016.05.006. Epub 2016 May 6. Phys Life Rev. 2016. PMID: 27173053 No abstract available.

6

A methodological approach for using high-level Petri Nets to model the immune system response.

Pennisi M, Cavalieri S, Motta S, Pappalardo F. Pennisi M, et al. BMC Bioinformatics. 2016 Dec 22;17(Suppl 19):498. doi: 10.1186/s12859-016-1361-6. BMC Bioinformatics. 2016. PMID: 28155706 Free PMC article.

7

Combining agent based-models and virtual screening techniques to predict the best citrus-derived vaccine adjuvants against human papilloma virus.

Pennisi M, Russo G, Ravalli S, Pappalardo F. Pennisi M, et al. BMC Bioinformatics. 2017 Dec 28;18(Suppl 16):544. doi: 10.1186/s12859-017-1961-9. BMC Bioinformatics. 2017. PMID: 29297294 Free PMC article.

8

Toward computational modelling on immune system function.

Pappalardo F, Pennisi M, Reche PA, Russo G. Pappalardo F, et al. Among authors: pennisi m. BMC Bioinformatics. 2019 Dec 10;20(Suppl 6):622. doi: 10.1186/s12859-019-3239-x. BMC Bioinformatics. 2019. PMID: 31823723 Free PMC article.

9

The Potential of Computational Modeling to Predict Disease Course and Treatment Response in Patients with Relapsing Multiple Sclerosis.

Pappalardo F, Russo G, Pennisi M, Parasiliti Palumbo GA, Sgroi G, Motta S, Maimone D. Pappalardo F, et al. Among authors: pennisi m. Cells. 2020 Mar 1;9(3):586. doi: 10.3390/cells9030586. Cells. 2020. PMID: 32121606 Free PMC article.

10

In silico trial to test COVID-19 candidate vaccines: a case study with UISS platform.

Russo G, Pennisi M, Fichera E, Motta S, Raciti G, Viceconti M, Pappalardo F. Russo G, et al. Among authors: pennisi m. BMC Bioinformatics. 2020 Dec 14;21(Suppl 17):527. doi: 10.1186/s12859-020-03872-0. BMC Bioinformatics. 2020. PMID: 33308153 Free PMC article.

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