Fernanda Fabiani

916 citations
21 papers · 731 · h-index 11

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
    • PI3K/AKT/mTOR signaling in cancer
    • RNA modifications and cancer

Papers in

    • PI3K/AKT/mTOR signaling in cancer 4
    • Cancer therapeutics and mechanisms 2
    • Epigenetics and DNA Methylation 2
    • Cancer-related Molecular Pathways 2

Fernanda Fabiani

20 papers receiving 724 citations

Peers

Fernanda Fabiani
Comparison fields: 5 of 73
  • Cancer Research 184
  • Molecular Biology 525
  • Hematology 76
  • Oncology 182
  • Pathology and Forensic Medicine 107
Replace William Dahut with:
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Nicoletta Staropoli Italy
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Shane K. Green Canada
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Citations per field
00.5×7.5×
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Citations per year

Countries citing papers authored by Fernanda Fabiani

Since Specialization
Citations

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

Fields of papers citing papers by Fernanda Fabiani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008146
2 2012126
3 2012101
4 200597
5 201172
6 201255
7 201331
8 200723
9 201923
10 201811
11 201510
12 20218
13 20148
14 20226
15 20116
16 20214
17 20211
18 20161
19 20121
20 20051

About Fernanda Fabiani

Fernanda Fabiani is a scholar working on Molecular Biology, Oncology, Pathology and Forensic Medicine, Cancer Research and Cell Biology, having authored 21 papers that have together received 731 indexed citations. Recurring topics across this work include PI3K/AKT/mTOR signaling in cancer (4 papers), Cancer therapeutics and mechanisms (2 papers), Skin and Cellular Biology Research (2 papers), MicroRNA in disease regulation (2 papers), Epigenetics and DNA Methylation (2 papers), BRCA gene mutations in cancer (2 papers), Hepatitis C virus research (2 papers) and Cancer-related Molecular Pathways (2 papers). The work is most often cited by research in Cancer Research (184 citations), Molecular Biology (525 citations), Hematology (76 citations), Oncology (182 citations) and Pathology and Forensic Medicine (107 citations). Fernanda Fabiani has collaborated with scholars based in Italy, United States and Russia. Frequent co-authors include Giuseppe Viglietto, Carmela De Marco, Renato Franco, Marianna Scrima, Donatella Malanga, Giuseppe Pirozzi, Gaetano Rocco, Pierfrancesco Tassone, Maria Teresa Di Martino and Michele Caraglia. Their work appears in journals such as Genes, Cell Cycle, PLoS ONE, Journal of Clinical Medicine and Clinical Pharmacology & Therapeutics.

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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