Davide Salzano

466 citations
16 papers · 240 indexed · h-index 8
Topics
Gene Regulatory Network Analysis (13 papers)Molecular Communication and Nanonetworks (6 papers)Bacterial Genetics and Biotechnology (4 papers)
Partner nations
ItalyUnited KingdomSpain

In The Last Decade

Davide Salzano

14 papers receiving 237 citations

Peers

Davide Salzano
Comparison fields: 5 of 55
  • Modeling and Simulation 115
  • Molecular Biology 102
  • Biomedical Engineering 52
  • Genetics 38
  • Infectious Diseases 38
Replace Tobias Brett with:
Tobias Brett United States
David Medina-Ortiz Chile
Atte Aalto Luxembourg
Joseph D. Challenger United Kingdom
Jiarui Sun China
Matthew Macauley United States
Xiao‐Bing Zhang China
Joan T. Matamalas United States
Tanmay Mitra Germany
Frederic Grabowski Poland
Davide Salzano relative to Tobias Brett United States Tobias Brett's profile →
Citations per field
00.5×6.5×
Tobias Brett · 1×
Citations per year

Countries citing papers authored by Davide Salzano

Since Specialization
Citations

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

Fields of papers citing papers by Davide Salzano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Davide Salzano

This figure shows the co-authorship network connecting the top 25 collaborators of Davide Salzano. A scholar is included among the top collaborators of Davide Salzano 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 Davide Salzano. Davide Salzano is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
#WorkIndexed citations
1 0
2 4
3 1
4 1
5 7
6 0
7 14
8 3
9 9
10 8
11 14
12 27
13 16
14 124
15 11
16 1

About Davide Salzano

Davide Salzano is a scholar working on Biophysics, Genetics and Modeling and Simulation, having authored 16 papers that have together received 240 indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (13 papers), Molecular Communication and Nanonetworks (6 papers) and Bacterial Genetics and Biotechnology (4 papers). The work is most often cited by research in Modeling and Simulation (115 citations), Statistical and Nonlinear Physics (29 citations) and Infectious Diseases (38 citations). Davide Salzano has collaborated with scholars based in Italy, United Kingdom and Spain. Frequent co-authors include Mario di Bernardo, Davide Fiore, Fabio Della Rossa, Giovanni Russo, Davide Liuzza, Francesco Lo Iudice, Pietro De Lellis, Lucia Marucci, Claire Grierson and Nigel J. Savery. Their work appears in journals such as Nature Communications, Journal of Hepatology and Journal of The Royal Society Interface.

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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