Anna De Blasio

1.5k citations
43 papers · 1.2k · h-index 24

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
  • Oncology top 10%
    • Cancer Cells and Metastasis
    • Cancer-related Molecular Pathways

Papers in

    • MicroRNA in disease regulation 6
    • Cancer-related Molecular Pathways 7
    • Cancer Cells and Metastasis 5

Anna De Blasio

42 papers receiving 1.2k citations

Peers

Anna De Blasio
Comparison fields: 5 of 103
  • Cancer Research 323
  • Oncology 263
  • Molecular Biology 599
  • Pharmacology 137
  • Hematology 92
Replace Jubo Wang with:
Jubo Wang China
Irfana Muqbil United States
Yasin Sheikh Ahmadi Iran
Wei‐En Yang Taiwan
Raffaella Dell’Eva Italy
Yule Chen China
Jiyeon Ahn South Korea
Mengqiu Song China
Baskaran Govindarajan United States
Zhong‐Fei Shen China
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Citations per field
00.5×2×4×5.5×
Jubo Wang · 1×
Citations per year

Countries citing papers authored by Anna De Blasio

Since Specialization
Citations

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

Fields of papers citing papers by Anna De Blasio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anna De Blasio. 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 Anna De Blasio. The network helps show where Anna De Blasio may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200981
2 201481
3 200864
4 201458
5 201757
6 201757
7 200447
8 201446
9 201846
10 201245
11 202041
12 201941
13 201040
14 201539
15 201237
16 201437
17 201437
18 202236
19 202034
20 202130

About Anna De Blasio

Anna De Blasio is a scholar working on Cancer Research, Oncology, Molecular Biology, Pharmacology and Complementary and alternative medicine, having authored 43 papers that have together received 1.2k indexed citations. Recurring topics across this work include Cell death mechanisms and regulation (8 papers), Cancer-related Molecular Pathways (7 papers), MicroRNA in disease regulation (6 papers), Autophagy in Disease and Therapy (5 papers), Cancer Cells and Metastasis (5 papers), Genomics, phytochemicals, and oxidative stress (5 papers), Cannabis and Cannabinoid Research (4 papers) and Endoplasmic Reticulum Stress and Disease (3 papers). The work is most often cited by research in Cancer Research (323 citations), Oncology (263 citations), Molecular Biology (599 citations), Pharmacology (137 citations) and Hematology (92 citations). Anna De Blasio has collaborated with scholars based in Italy, United States and Malta. Frequent co-authors include Renza Vento, Michela Giuliano, Riccardo Di Fiore, Daniela Carlisi, Giovanni Tesoriere, Antonella D’Anneo, Giuseppe Calvaruso, Sonia Emanuele, Marianna Lauricella and Rosa Drago‐Ferrante. Their work appears in journals such as International Journal of Molecular Sciences, Journal of Cellular Physiology, International Journal of Oncology, Antioxidants and Biomedicines.

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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