Daniela Segat

1.0k citations
32 papers · 852 · h-index 19

Impact in

Papers in

    • Glycosylation and Glycoproteins Research 2
    • Metabolism, Diabetes, and Cancer 2
    • Proteoglycans and glycosaminoglycans research 3

Daniela Segat

32 papers receiving 840 citations

Peers

Daniela Segat
Comparison fields: 5 of 101
  • Immunology and Allergy 96
  • Cell Biology 165
  • Biomaterials 133
  • Microbiology 40
  • Surfaces, Coatings and Films 41
Replace Valeryi K. Lishko with:
Valeryi K. Lishko United States
Emmett Pinney United States
Cinzia Zucchini Italy
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Dennis W. Zhou United States
Keizo Yamamura Japan
Susanne Schenk Switzerland
Yanlun Gu China
Kazuyuki Mori Japan
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Citations per field
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Citations per year

Countries citing papers authored by Daniela Segat

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Segat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005118
2 201560
3 200854
4 201553
5 201049
6 200246
7 201043
8 200438
9 200338
10 199231
11 200031
12 200229
13 201126
14 201423
15 201022
16 201122
17 199420
18 200920
19 201019
20 201217

About Daniela Segat

Daniela Segat is a scholar working on Molecular Biology, Cell Biology, Immunology and Allergy, Surgery and Oncology, having authored 32 papers that have together received 852 indexed citations. Recurring topics across this work include Cell Adhesion Molecules Research (7 papers), Soft tissue tumor case studies (3 papers), Proteoglycans and glycosaminoglycans research (3 papers), Glycosylation and Glycoproteins Research (2 papers), Osteoarthritis Treatment and Mechanisms (2 papers), Metabolism, Diabetes, and Cancer (2 papers), Cancer Diagnosis and Treatment (2 papers) and HER2/EGFR in Cancer Research (2 papers). The work is most often cited by research in Immunology and Allergy (96 citations), Cell Biology (165 citations), Biomaterials (133 citations), Microbiology (40 citations) and Surfaces, Coatings and Films (41 citations). Daniela Segat has collaborated with scholars based in Italy, Germany and Slovenia. Frequent co-authors include Regina Tavano, Emanuele Papini, Fabrizio Mancin, Francesco Selvestrel, Carlo Tacchetti, Renzo Cordera, Davide Maggi, Uroš Hladnik, Marco Rastrelli and Daniela Tosoni. Their work appears in journals such as Nanomedicine, Matrix Biology, Blood, Journal of Biological Chemistry and Biochemical and Biophysical Research Communications.

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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