Daniela Verzella

2.4k citations
34 papers · 1.7k · 2 hit papers · h-index 19

Impact in

    • MicroRNA in disease regulation
    • NF-κB Signaling Pathways
    • Cancer-related molecular mechanisms research
  • Immunology top 5%
    • Immune cells in cancer
    • Immune Cell Function and Interaction

Papers in

Daniela Verzella

33 papers receiving 1.7k citations

Daniela Verzella's Hit Papers

NF-κB: blending metabolism, immunity, and inflammation 2022 · 353 citations
3530+2+4Years since publication100200300

Peers

Daniela Verzella
Comparison fields: 5 of 107
  • Cancer Research 441
  • Immunology 484
  • Oncology 313
  • Hepatology 78
  • Molecular Biology 738
Replace Daria Capece with:
Daria Capece Italy
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Daniela Verzella relative to Daria Capece Italy Daria Capece's profile →
Citations per field
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Daria Capece · 1×
Citations per year

Countries citing papers authored by Daniela Verzella

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Verzella

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1
NF-κB: blending metabolism, immunity, and inflammation
Hit paper breakdown →
2022353
2 2012330
3
Life, death, and autophagy in cancer: NF-κB turns up everywhere
Hit paper breakdown →
2020260
4 201280
5 201675
6 201772
7 201461
8 202456
9 201952
10 201750
11 201745
12 201638
13 201334
14 202230
15 201830
16
201825
17 201522
18 201521
19 202220
20 201413

About Daniela Verzella

Daniela Verzella is a scholar working on Molecular Biology, Cancer Research, Immunology, Oncology and Epidemiology, having authored 34 papers that have together received 1.7k indexed citations. Recurring topics across this work include NF-κB Signaling Pathways (8 papers), Immune cells in cancer (6 papers), interferon and immune responses (4 papers), MicroRNA in disease regulation (4 papers), Circular RNAs in diseases (3 papers), Cancer Immunotherapy and Biomarkers (3 papers), Immune Cell Function and Interaction (3 papers) and Epigenetics and DNA Methylation (3 papers). The work is most often cited by research in Cancer Research (441 citations), Immunology (484 citations), Oncology (313 citations), Hepatology (78 citations) and Molecular Biology (738 citations). Daniela Verzella has collaborated with scholars based in Italy, United Kingdom and France. Frequent co-authors include Daria Capece, Francesca Zazzeroni, Edoardo Alesse, Guido Franzoso, Mariafausta Fischietti, Alessandra Tessitore, Jessica Cornice, Irene Flati, Davide Vecchiotti and Germana Cicciarelli. Their work appears in journals such as Genes, BioMed Research International, Biomedicines, Cancers and Seminars in Cell and Developmental 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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