Francesco Pappalardo

4.3k total citations
128 papers, 2.6k citations indexed

About

Francesco Pappalardo is a scholar working on Molecular Biology, Immunology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Francesco Pappalardo has authored 128 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 72 papers in Molecular Biology, 38 papers in Immunology and 17 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Francesco Pappalardo's work include vaccines and immunoinformatics approaches (34 papers), Gene Regulatory Network Analysis (24 papers) and Immunotherapy and Immune Responses (20 papers). Francesco Pappalardo is often cited by papers focused on vaccines and immunoinformatics approaches (34 papers), Gene Regulatory Network Analysis (24 papers) and Immunotherapy and Immune Responses (20 papers). Francesco Pappalardo collaborates with scholars based in Italy, United Kingdom and United States. Francesco Pappalardo's co-authors include Santo Motta, Marzio Pennisi, Giulia Russo, Marco Viceconti, Flora T. Musuamba, Pier‐Luigi Lollini, Filippo Castiglione, Ferdınando Chıacchıo, Blanca Rodríguez and Carlo Bianca and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and PLoS ONE.

In The Last Decade

Francesco Pappalardo

120 papers receiving 2.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Francesco Pappalardo Italy 30 1.1k 468 342 309 251 128 2.6k
Hongyu Miao United States 30 1.0k 0.9× 459 1.0× 377 1.1× 219 0.7× 119 0.5× 121 3.7k
Gary An United States 35 1.5k 1.3× 609 1.3× 358 1.0× 108 0.3× 559 2.2× 176 4.2k
Clemens Kreutz Germany 32 2.1k 1.9× 287 0.6× 221 0.6× 81 0.3× 277 1.1× 84 3.8k
Andreas Raue Germany 23 1.8k 1.6× 311 0.7× 248 0.7× 86 0.3× 338 1.3× 44 3.0k
Marzio Pennisi Italy 24 613 0.6× 258 0.6× 240 0.7× 125 0.4× 134 0.5× 77 1.3k
Giulia Russo Italy 25 573 0.5× 191 0.4× 87 0.3× 169 0.5× 151 0.6× 113 1.9k
Mrinal K. Ghosh India 38 1.9k 1.7× 310 0.7× 178 0.5× 60 0.2× 668 2.7× 183 4.8k
Yuan Yuan China 42 2.1k 1.9× 591 1.3× 153 0.4× 331 1.1× 822 3.3× 393 6.5k
Seiya Imoto Japan 39 4.5k 4.1× 622 1.3× 125 0.4× 133 0.4× 693 2.8× 284 7.0k
Hulin Wu United States 41 1.1k 1.0× 580 1.2× 477 1.4× 114 0.4× 137 0.5× 184 5.5k

Countries citing papers authored by Francesco Pappalardo

Since Specialization
Citations

This map shows the geographic impact of Francesco Pappalardo'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 Francesco Pappalardo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Francesco Pappalardo more than expected).

Fields of papers citing papers by Francesco Pappalardo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Francesco Pappalardo. 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 Francesco Pappalardo. The network helps show where Francesco Pappalardo may publish in the future.

Co-authorship network of co-authors of Francesco Pappalardo

This figure shows the co-authorship network connecting the top 25 collaborators of Francesco Pappalardo. A scholar is included among the top collaborators of Francesco Pappalardo 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 Francesco Pappalardo. Francesco Pappalardo 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.
Aldieri, Alessandra, et al.. (2025). Consensus statement on the credibility assessment of machine learning predictors. Briefings in Bioinformatics. 26(2). 1 indexed citations
2.
Russo, Giulia, et al.. (2025). In-silico epitope-based vaccines design: progress, challenges and the road ahead. Expert Opinion on Drug Discovery. 20(12). 1701–1712.
3.
Pistollato, Francesca, et al.. (2025). Advancing the frontier of rare disease modeling: a critical appraisal of in silico technologies. npj Digital Medicine. 8(1). 676–676.
4.
Puglisi, Roberta, Antonino Gulino, Valentina Oliveri, et al.. (2024). Dopamine sensing by fluorescent carbon nanoparticles synthesized using artichoke extract. Journal of Materials Chemistry B. 12(32). 7826–7836. 5 indexed citations
5.
6.
Bonaccorso, Angela, Giulia Russo, Francesco Pappalardo, et al.. (2021). Quality by design tools reducing the gap from bench to bedside for nanomedicine. European Journal of Pharmaceutics and Biopharmaceutics. 169. 144–155. 23 indexed citations
7.
Russo, Giulia, et al.. (2021). A multi-step and multi-scale bioinformatic protocol to investigate potential SARS-CoV-2 vaccine targets. Briefings in Bioinformatics. 23(1). 25 indexed citations
8.
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
9.
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
10.
Catanuto, Giuseppe, Francesco Pappalardo, Nicola Rocco, et al.. (2016). Formal analysis of the surgical pathway and development of a new software tool to assist surgeons in the decision making in primary breast surgery. The Breast. 29. 74–81. 10 indexed citations
11.
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
12.
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
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, 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
15.
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
16.
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
17.
Palladini, Arianna, Giordano Nicoletti, Francesco Pappalardo, et al.. (2010). In silico Modeling and In vivo Efficacy of Cancer-Preventive Vaccinations. Cancer Research. 70(20). 7755–7763. 69 indexed citations
18.
Pappalardo, Francesco, et al.. (2009). HAMFAST: Fast Hamming Distance Computation. 569–572. 6 indexed citations
19.
Lollini, Pier‐Luigi, Santo Motta, & Francesco Pappalardo. (2006). MODELING TUMOR IMMUNOLOGY. Mathematical Models and Methods in Applied Sciences. 16(supp01). 1091–1124. 25 indexed citations
20.
Motta, Santo, Filippo Castiglione, Pier‐Luigi Lollini, & Francesco Pappalardo. (2005). Modelling vaccination schedules for a cancer immunoprevention vaccine.. PubMed. 1(1). 5–5. 22 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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