Marzio Pennisi

2.0k total citations
77 papers, 1.3k citations indexed

About

Marzio Pennisi is a scholar working on Molecular Biology, Immunology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Marzio Pennisi has authored 77 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Molecular Biology, 21 papers in Immunology and 14 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Marzio Pennisi's work include Gene Regulatory Network Analysis (22 papers), vaccines and immunoinformatics approaches (21 papers) and Immunotherapy and Immune Responses (13 papers). Marzio Pennisi is often cited by papers focused on Gene Regulatory Network Analysis (22 papers), vaccines and immunoinformatics approaches (21 papers) and Immunotherapy and Immune Responses (13 papers). Marzio Pennisi collaborates with scholars based in Italy, United Kingdom and United States. Marzio Pennisi's co-authors include Francesco Pappalardo, Santo Motta, Giulia Russo, Carlo Bianca, Ferdınando Chıacchıo, Maria Alessandra Ragusa, Marco Viceconti, Filippo Castiglione, Miguel A. Juárez and Pedro A. Reche and has published in prestigious journals such as Bioinformatics, PLoS ONE and Expert Systems with Applications.

In The Last Decade

Marzio Pennisi

76 papers receiving 1.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Marzio Pennisi Italy 24 613 258 240 134 125 77 1.3k
Giulia Russo Italy 25 573 0.9× 191 0.7× 87 0.4× 151 1.1× 169 1.4× 113 1.9k
Marcel Schilling Germany 17 1.4k 2.2× 176 0.7× 179 0.7× 225 1.7× 51 0.4× 31 2.2k
Francesco Pappalardo Italy 30 1.1k 1.8× 468 1.8× 342 1.4× 251 1.9× 309 2.5× 128 2.6k
Andreas Raue Germany 23 1.8k 2.9× 311 1.2× 248 1.0× 338 2.5× 86 0.7× 44 3.0k
Xiaoxiao Lu China 22 648 1.1× 187 0.7× 64 0.3× 183 1.4× 50 0.4× 98 1.6k
Chengjun Sun China 21 1.2k 1.9× 132 0.5× 423 1.8× 78 0.6× 186 1.5× 72 2.6k
Fabien Crauste France 18 303 0.5× 255 1.0× 262 1.1× 88 0.7× 24 0.2× 51 1.1k
Neil D. Evans United Kingdom 21 647 1.1× 59 0.2× 130 0.5× 170 1.3× 44 0.4× 97 1.5k
Scott Christley United States 23 712 1.2× 352 1.4× 48 0.2× 221 1.6× 134 1.1× 57 1.5k

Countries citing papers authored by Marzio Pennisi

Since Specialization
Citations

This map shows the geographic impact of Marzio Pennisi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Marzio Pennisi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marzio Pennisi more than expected).

Fields of papers citing papers by Marzio Pennisi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marzio Pennisi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Marzio Pennisi. The network helps show where Marzio Pennisi may publish in the future.

Co-authorship network of co-authors of Marzio Pennisi

This figure shows the co-authorship network connecting the top 25 collaborators of Marzio Pennisi. A scholar is included among the top collaborators of Marzio Pennisi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Marzio Pennisi. Marzio Pennisi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Valdembri, Donatella, Guido Serini, Federica Riccardo, et al.. (2023). OmniReprodubileCellAnalysis: a comprehensive toolbox for the analysis of cellular biology data. 1 indexed citations
3.
Bottrighi, Alessio & Marzio Pennisi. (2023). Exploring the State of Machine Learning and Deep Learning in Medicine: A Survey of the Italian Research Community. Information. 14(9). 513–513. 3 indexed citations
4.
Betti, Marta, Marinella Bertolotti, Alessio Bottrighi, et al.. (2021). A Preliminary Analysis of Hospitalized Covid-19 Patients in Alessandria Area: a machine learning approach. 368. 1–6. 1 indexed citations
5.
Russo, Giulia, Marzio Pennisi, Santo Motta, et al.. (2020). In silico trial to test COVID-19 candidate vaccines: a case study with UISS platform. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 33 indexed citations
6.
Maglione, Alessandro, Marzio Pennisi, Francesco Pappalardo, et al.. (2020). Computational modeling of the immune response in multiple sclerosis using epimod framework. BMC Bioinformatics. 21(S17). 550–550. 11 indexed citations
7.
Pennisi, Marzio, et al.. (2019). Generation of digital patients for the simulation of tuberculosis with UISS-TB. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 2 indexed citations
8.
Gianì, Fiorenza, Giulia Russo, Marzio Pennisi, et al.. (2018). Computational modeling reveals MAP3K8 as mediator of resistance to vemurafenib in thyroid cancer stem cells. Bioinformatics. 35(13). 2267–2275. 26 indexed citations
9.
Pappalardo, Francesco, Giulia Russo, Saverio Candido, et al.. (2016). Computational Modeling of PI3K/AKT and MAPK Signaling Pathways in Melanoma Cancer. PLoS ONE. 11(3). e0152104–e0152104. 47 indexed citations
10.
Pennisi, Marzio, Giulia Russo, Santo Motta, & Francesco Pappalardo. (2015). Agent based modeling of the effects of potential treatments over the blood–brain barrier in multiple sclerosis. Journal of Immunological Methods. 427. 6–12. 19 indexed citations
11.
Pennisi, Marzio, et al.. (2014). In Silico Modeling of the Immune System: Cellular and Molecular Scale Approaches. BioMed Research International. 2014. 1–7. 7 indexed citations
12.
Pappalardo, Francesco, Marzio Pennisi, Alessia Ricupito, Francesco Topputo, & Matteo Bellone. (2014). Induction of T-cell memory by a dendritic cell vaccine: a computational model. Bioinformatics. 30(13). 1884–1891. 31 indexed citations
13.
Bianca, Carlo, Francesco Pappalardo, Marzio Pennisi, & Maria Alessandra Ragusa. (2013). Persistence analysis in a Kolmogorov-type model for cancer-immune system competition. AIP conference proceedings. 1797–1800. 53 indexed citations
14.
Bianca, Carlo & Marzio Pennisi. (2012). Immune system modelling by top-down and bottom-up approaches. Haematologica. 7(8). 109–128. 11 indexed citations
15.
Bianca, Carlo, Ferdınando Chıacchıo, Francesco Pappalardo, & Marzio Pennisi. (2012). Mathematical modeling of the immune system recognition to mammary carcinoma antigen. BMC Bioinformatics. 13(S17). S21–S21. 36 indexed citations
16.
Pennisi, Marzio, Carlo Bianca, Francesco Pappalardo, & Santo Motta. (2011). Compartmental mathematical modeling of immune system - melanoma competition. PORTO Publications Open Repository TOrino (Politecnico di Torino). 930–934. 3 indexed citations
17.
Pennisi, Marzio, Carlo Bianca, Francesco Pappalardo, & Santo Motta. (2010). Modeling artificial immunity against mammary carcinoma. PORTO Publications Open Repository TOrino (Politecnico di Torino). 4 indexed citations
18.
Pennisi, Marzio, Francesco Pappalardo, Giordano Nicoletti, et al.. (2010). Modeling the competition between lung metastases and the immune system using agents. BMC Bioinformatics. 11(S7). S13–S13. 52 indexed citations
19.
Pappalardo, Francesco, et al.. (2009). HAMFAST: Fast Hamming Distance Computation. 569–572. 6 indexed citations
20.
Pennisi, Marzio, et al.. (2005). Non-invasive Ventilation in Immunocompromised Patients. PubMed. 77(3). 201–209. 8 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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