Daniela Modena

42 papers receiving 886 citations

Peers

Daniela Modena
Comparison fields: 5 of 91
  • Biotechnology 169
  • Immunology 225
  • Molecular Biology 631
  • Physiology 30
  • Hematology 67
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Alexandre Fontayne France
Pernille Holm Denmark
Satoshi ŌMURA Japan
Claudia Scotti Italy
D E Wylie United States
Stanisław Szala Poland
Masaru Koyama Japan
Stephen R. Hamilton United States
Mark Whitmore United States
Monica Loi Italy
Daniela Modena relative to Alexandre Fontayne France Alexandre Fontayne's profile →
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Citations per year

Countries citing papers authored by Daniela Modena

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Modena

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005279
2 201187
3 201451
4 198645
5 198638
6 199135
7
Delivery of saporin to human B-cell lymphoma using bispecific antibody: targeting via CD22 but not CD19, CD37, or immunoglobulin results in efficient killing.
199334
8 198632
9 198031
10
Initial experience in treating human lymphoma with a combination of bispecific antibody and saporin.
199223
11 201922
12 200220
13 199319
14 198219
15 199517
16 199516
17 201616
18 201416
19 199414
20
Heterologous expression, purification, activity and conformational studies of different forms of dianthin 30.
19958

About Daniela Modena

Daniela Modena is a scholar working on Biotechnology, Biochemistry, Immunology, Clinical Biochemistry and Radiology, Nuclear Medicine and Imaging, having authored 44 papers that have together received 908 indexed citations. Recurring topics across this work include Toxin Mechanisms and Immunotoxins (10 papers), Transgenic Plants and Applications (7 papers), Monoclonal and Polyclonal Antibodies Research (6 papers), Heat shock proteins research (6 papers), Amino Acid Enzymes and Metabolism (6 papers), Protein Structure and Dynamics (5 papers), Polyamine Metabolism and Applications (5 papers) and Peptidase Inhibition and Analysis (4 papers). The work is most often cited by research in Biotechnology (169 citations), Immunology (225 citations), Molecular Biology (631 citations), Physiology (30 citations) and Hematology (67 citations). Daniela Modena has collaborated with scholars based in Italy, United States and Netherlands. Frequent co-authors include Gianluca Fossati, Paolo Mascagni, Charles A. Dinarello, Leonid L. Reznikov, Flavio Leoni, Julius Marmur, Giulia Porro, Gianni Gromo, Pietro Pozzi and Paolo Pagani. Their work appears in journals such as Cancer Immunology Immunotherapy, Molecular Medicine, Biochemical and Biophysical Research Communications, Carcinogenesis and Physics in Medicine and Biology.

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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