Daniela de Totero

1.3k total citations
42 papers, 995 citations indexed

About

Daniela de Totero is a scholar working on Immunology, Genetics and Molecular Biology. According to data from OpenAlex, Daniela de Totero has authored 42 papers receiving a total of 995 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Immunology, 14 papers in Genetics and 12 papers in Molecular Biology. Recurrent topics in Daniela de Totero's work include Chronic Lymphocytic Leukemia Research (14 papers), Immune Cell Function and Interaction (13 papers) and Lymphoma Diagnosis and Treatment (8 papers). Daniela de Totero is often cited by papers focused on Chronic Lymphocytic Leukemia Research (14 papers), Immune Cell Function and Interaction (13 papers) and Lymphoma Diagnosis and Treatment (8 papers). Daniela de Totero collaborates with scholars based in Italy, Germany and France. Daniela de Totero's co-authors include Silvano Ferrini, Marco Gobbi, Marina Fabbi, Enrico Balleari, Pier Luigi Tazzari, Giovanna Cutrona, Maurizio Viale, Raffaella Meazza, Matteo Capaia and Manlio Ferrarini and has published in prestigious journals such as Blood, International Journal of Molecular Sciences and Journal of Controlled Release.

In The Last Decade

Daniela de Totero

41 papers receiving 968 citations

Peers

Daniela de Totero
Comparison fields: 5 of 91
  • Immunology 506
  • Genetics 260
  • Molecular Biology 252
  • Oncology 245
  • Pathology and Forensic Medicine 219
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Citations per field, relative to Daniela de Totero
Daniela de Totero · 1×
Citations per year, relative to Daniela de Totero
Daniela de Totero · 1×

Countries citing papers authored by Daniela de Totero

Since Specialization
Citations

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

Fields of papers citing papers by Daniela de Totero

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniela de Totero

This figure shows the co-authorship network connecting the top 25 collaborators of Daniela de Totero. A scholar is included among the top collaborators of Daniela de Totero 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 Daniela de Totero. Daniela de Totero 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
# Work Indexed citations
1 4
2 3
3 3
4 6
5 10
6 8
7 4
8 13
9 32
10 15
11 133
12 29
13 13
14
An Epstein-Barr virus-infected lymphoblastoid cell line (D430B) that grows in SCID-mice with the morphologic features of a CD30+ anaplastic large cell lymphoma, and is sensitive to anti-CD30 immunotoxins.
26
15 56
16
Expression of the IL2 receptor α, β and γ chains in hairy cell leukemia
4
17 3
18 18
19 70
20 1

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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