Paolo Perlasca

1.0k total citations
20 papers, 590 citations indexed

About

Paolo Perlasca is a scholar working on Artificial Intelligence, Sociology and Political Science and Molecular Biology. According to data from OpenAlex, Paolo Perlasca has authored 20 papers receiving a total of 590 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 8 papers in Sociology and Political Science and 7 papers in Molecular Biology. Recurrent topics in Paolo Perlasca's work include Access Control and Trust (7 papers), Bioinformatics and Genomic Networks (6 papers) and Cryptography and Data Security (5 papers). Paolo Perlasca is often cited by papers focused on Access Control and Trust (7 papers), Bioinformatics and Genomic Networks (6 papers) and Cryptography and Data Security (5 papers). Paolo Perlasca collaborates with scholars based in Italy, United States and Switzerland. Paolo Perlasca's co-authors include Elisa Bertino, Barbara Catania, Maria Luisa Damiani, Elena Ferrari, Marco Mesiti, Giorgio Valentini, Ismael Sanz, Ernesto Jiménez-Ruiz, David Manset and Rafael Berlanga and has published in prestigious journals such as PLoS ONE, Scientific Reports and IEEE Access.

In The Last Decade

Paolo Perlasca

17 papers receiving 557 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Paolo Perlasca Italy 8 443 441 187 155 36 20 590
Jeremy Jacob United Kingdom 12 321 0.7× 124 0.3× 219 1.2× 170 1.1× 22 0.6× 25 484
John Barkley United States 9 417 0.9× 509 1.2× 248 1.3× 163 1.1× 5 0.1× 19 609
Anna Lisa Ferrara Italy 13 352 0.8× 120 0.3× 100 0.5× 130 0.8× 42 1.2× 25 453
Vacha Dave United States 9 300 0.7× 76 0.2× 227 1.2× 170 1.1× 15 0.4× 12 515
Stéphanie Delaune France 14 467 1.1× 90 0.2× 338 1.8× 367 2.4× 12 0.3× 48 602
Carl Ellison United States 10 338 0.8× 307 0.7× 256 1.4× 214 1.4× 4 0.1× 18 562
Daniel Slamanig Austria 12 460 1.0× 61 0.1× 351 1.9× 134 0.9× 6 0.2× 50 583
Byoungcheon Lee South Korea 12 281 0.6× 51 0.1× 132 0.7× 138 0.9× 29 0.8× 25 391
Adam Bender United States 8 473 1.1× 182 0.4× 153 0.8× 308 2.0× 8 0.2× 12 675
Shyhtsun Felix Wu United States 10 183 0.4× 48 0.1× 153 0.8× 157 1.0× 12 0.3× 22 341

Countries citing papers authored by Paolo Perlasca

Since Specialization
Citations

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

Fields of papers citing papers by Paolo Perlasca

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Paolo Perlasca

This figure shows the co-authorship network connecting the top 25 collaborators of Paolo Perlasca. A scholar is included among the top collaborators of Paolo Perlasca 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 Paolo Perlasca. Paolo Perlasca 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.
Soto, Mauricio, Paolo Perlasca, Jessica Gliozzo, et al.. (2024). An ontology-based knowledge graph for representing interactions involving RNA molecules. Scientific Data. 11(1). 906–906. 7 indexed citations
2.
Mesiti, Marco, et al.. (2023). Indexing Structures for the Efficient Multi-Resolution Visualization of Big Graphs. IEEE Access. 11. 103585–103600. 1 indexed citations
3.
Gliozzo, Jessica, Paolo Perlasca, Marco Mesiti, et al.. (2020). Network modeling of patients' biomolecular profiles for clinical phenotype/outcome prediction. Scientific Reports. 10(1). 3612–3612. 7 indexed citations
4.
Perlasca, Paolo, Marco Frasca, Jessica Gliozzo, et al.. (2020). Multi-resolution visualization and analysis of biomolecular networks through hierarchical community detection and web-based graphical tools. PLoS ONE. 15(12). e0244241–e0244241. 6 indexed citations
5.
Perlasca, Paolo, Marco Frasca, Marco Notaro, et al.. (2019). UNIPred-Web: a web tool for the integration and visualization of biomolecular networks for protein function prediction. BMC Bioinformatics. 20(1). 422–422. 6 indexed citations
6.
Frasca, Marco, Giuliano Grossi, Jessica Gliozzo, et al.. (2018). A GPU-based algorithm for fast node label learning in large and unbalanced biomolecular networks. BMC Bioinformatics. 19(S10). 353–353. 1 indexed citations
7.
Ottaviani, Giulia, Paolo Perlasca, Marco Mesiti, Luca Ferrari, & Anna Maria Lavezzi. (2017). Authorised access web portal for Italian data bank on sudden unexpected perinatal and infant death. Acta Paediatrica. 106(7). 1196–1197. 2 indexed citations
8.
Bellini, Pierfrancesco, Marco Mesiti, Paolo Nesi, & Paolo Perlasca. (2017). Protection and composition of crossmedia content in collaborative environments. Multimedia Tools and Applications. 77(2). 2083–2114. 4 indexed citations
9.
Perlasca, Paolo, Giorgio Valentini, Marco Frasca, & Marco Mesiti. (2016). Multi-species protein function prediction. 489–493. 2 indexed citations
10.
Baratè, Adriano, Goffredo Haus, Luca A. Ludovico, & Paolo Perlasca. (2015). Managing Intellectual Property in a Music Fruition Environment. IEEE Multimedia. 23(2). 84–94. 6 indexed citations
11.
Mesiti, Marco, Alessandro Pellegata, & Paolo Perlasca. (2014). Making the Analysis of the Italian Legislative System Easy: The ILMA Web Portal. Journal of Information Technology & Politics. 12(1). 88–102.
12.
Mesiti, Marco, Ernesto Jiménez-Ruiz, Ismael Sanz, et al.. (2009). XML-based approaches for the integration of heterogeneous bio-molecular data. BMC Bioinformatics. 10(S12). S7–S7. 29 indexed citations
13.
Damiani, Maria Luisa, Elisa Bertino, Barbara Catania, & Paolo Perlasca. (2007). GEO-RBAC. ACM Transactions on Information and System Security. 10(1). 2–2. 101 indexed citations
14.
Damiani, Maria Luisa, Elisa Bertino, & Paolo Perlasca. (2007). Data security in location-aware applications: an approach based on RBAC. International Journal of Information and Computer Security. 1(1/2). 5–5. 11 indexed citations
15.
Bertino, Elisa, Barbara Catania, Maria Luisa Damiani, & Paolo Perlasca. (2005). GEO-RBAC. Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano). 29–37. 228 indexed citations
16.
Bertino, Elisa, Barbara Catania, Elena Ferrari, & Paolo Perlasca. (2004). On comparing the expressing power of access control model frameworks. 283–299.
17.
Bertino, Elisa, Barbara Catania, Elena Ferrari, & Paolo Perlasca. (2003). A system to specify and manage multipolicy access control models. 116–127. 26 indexed citations
18.
Bertino, Elisa, Barbara Catania, Elena Ferrari, & Paolo Perlasca. (2003). A logical framework for reasoning about access control models. ACM Transactions on Information and System Security. 6(1). 71–127. 117 indexed citations
19.
Bertino, Elisa, Barbara Catania, Elena Ferrari, & Paolo Perlasca. (2001). A logical framework for reasoning about access control models. 41–52. 36 indexed citations
20.
Bertino, Elisa, Barbara Catania, & Paolo Perlasca. (2001). Introducing cooperation and actions in amalgamated knowledge bases. 108–115.

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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