F. Cavalièri

20 papers receiving 414 citations

Peers

F. Cavalièri
Comparison fields: 5 of 64
  • Virology 20
  • Infectious Diseases 75
  • Genetics 106
  • Microbiology 23
  • Epidemiology 116
Replace Louis E.-C. Leong with:
Louis E.-C. Leong Singapore
Christina Kämmer Germany
P. Sondermeyer France
Kunio Kondo Japan
M. R. Stebbins United States
W. I. H. Shedden United Kingdom
R. Grob Switzerland
Daniel T. Passos Canada
Gek-Kee Sim United States
Norman B. Darby United States
F. Cavalièri relative to Louis E.-C. Leong Singapore Louis E.-C. Leong's profile →
Citations per field
00.5×1.5×1.9×
Louis E.-C. Leong · 1×
Citations per year

Countries citing papers authored by F. Cavalièri

Since Specialization
Citations

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

Fields of papers citing papers by F. Cavalièri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside F. Cavalièri, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with F. Cavalièri Line = papers co-authored together F. Cavalièri links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1
HPV16 E7 protein associates with the protein kinase p33CDK2 and cyclin A.
1993107
2 199296
3 198740
4 198537
5 199026
6 199123
7
N-myc proto-oncogene expression can induce DNA replication in Balb/c 3T3 fibroblasts.
198820
8 198119
9 199617
10 199210
11 198110
12 198010
13 19964
14 19913
15 19833
16 19922
17
[Presence of enteric viruses in non-diarrheic canine stools].
19802
18 19841
19
Characteristics of three new avian sarcoma viruses, ASV 9, ASV 17, and ASV 25.
19841
20
Secretion of heterologous proteins in Streptococcus gordonii (Streptococcus sanguis) Challis.
19931

About F. Cavalièri

F. Cavalièri is a scholar working on Molecular Biology, Genetics, Animal Science and Zoology, Epidemiology and Infectious Diseases, having authored 21 papers that have together received 433 indexed citations. Recurring topics across this work include Virus-based gene therapy research (7 papers), Animal Virus Infections Studies (6 papers), Plant Virus Research Studies (4 papers), Viral gastroenteritis research and epidemiology (4 papers), Cervical Cancer and HPV Research (3 papers), Hepatitis B Virus Studies (2 papers), Molecular Biology Techniques and Applications (2 papers) and CRISPR and Genetic Engineering (2 papers). The work is most often cited by research in Virology (20 citations), Infectious Diseases (75 citations), Genetics (106 citations), Microbiology (23 citations) and Epidemiology (116 citations). F. Cavalièri has collaborated with scholars based in France, Italy and United States. Frequent co-authors include Mario Contorni, Massimo Tommasino, Mitchell Goldfarb, Marco R. Oggioni, Riccardo Manganelli, Gianni Pozzi, Vincent A. Fischetti, C F Barth, Tim Hunt and Françoise Carlotti. Their work appears in journals such as Archives of Virology, Gene, Critical Reviews in Eukaryotic Gene Expression, Journal of Hepatology and Journal of General Virology.

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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