Daniela Salvatori

3.0k citations
73 papers · 1.7k · h-index 24

Impact in

Papers in

    • Renal and related cancers 9
    • Pluripotent Stem Cells Research 9
    • CRISPR and Genetic Engineering 6
    • Wnt/β-catenin signaling in development and cancer 4
    • Herpesvirus Infections and Treatments 10

Daniela Salvatori

68 papers receiving 1.6k citations

Peers

Daniela Salvatori
Comparison fields: 5 of 111
  • Microbiology 60
  • Immunology 301
  • Small Animals 104
  • Molecular Biology 768
  • Cancer Research 134
Replace Manuela Mura with:
Manuela Mura Italy
Narsing A. Rao United States
Flavio Lejbkowicz Israel
Helen Spencer United Kingdom
Elizabeth W. Uhl United States
Kazuyoshi Hashizume Japan
Yutaka NARISAWA Japan
Xiaowu Gai United States
A. von Herbay Germany
G Cordier France
Daniela Salvatori relative to Manuela Mura Italy Manuela Mura's profile →
Citations per field
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Manuela Mura · 1×
Citations per year

Countries citing papers authored by Daniela Salvatori

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Salvatori

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniela Salvatori, 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 Daniela Salvatori Line = papers co-authored together Daniela Salvatori links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 73 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012204
2 2019122
3 2015101
4 201188
5 201366
6 201062
7 201261
8 201858
9 200454
10 201644
11 201338
12 200938
13 201737
14 200534
15 201734
16 201232
17 201430
18 200230
19 201430
20 201327

About Daniela Salvatori

Daniela Salvatori is a scholar working on Molecular Biology, Epidemiology, Immunology, Oncology and Surgery, having authored 73 papers that have together received 1.7k indexed citations. Recurring topics across this work include Herpesvirus Infections and Treatments (10 papers), Renal and related cancers (9 papers), Pluripotent Stem Cells Research (9 papers), T-cell and Retrovirus Studies (6 papers), CRISPR and Genetic Engineering (6 papers), HIV Research and Treatment (5 papers), Vector-Borne Animal Diseases (4 papers) and Wnt/β-catenin signaling in development and cancer (4 papers). The work is most often cited by research in Microbiology (60 citations), Immunology (301 citations), Small Animals (104 citations), Molecular Biology (768 citations) and Cancer Research (134 citations). Daniela Salvatori has collaborated with scholars based in Netherlands, Italy and United States. Frequent co-authors include Christine L. Mummery, Christian Freund, Els C. Robanus-Maandag, Richard P. Davis, Simona Casini, Carol Ann Remme, Maaike Hoekstra, Dorien Ward‐van Oostwaard, Arthur A.M. Wilde and Cheryl Dambrot. Their work appears in journals such as Comparative Immunology Microbiology and Infectious Diseases, Stem Cell Reports, Blood, International Journal of Molecular Sciences and Journal of Lipid Research.

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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