Sara Nava

1.4k citations
29 papers · 894 · h-index 18

Impact in

  • Genetics top 5%
    • Glioma Diagnosis and Treatment
    • Mesenchymal stem cell research
  • Oncology top 10%
    • Cancer Cells and Metastasis
    • Cancer Immunotherapy and Biomarkers
    • CAR-T cell therapy research

Papers in

    • CAR-T cell therapy research 7
    • Cancer Cells and Metastasis 5
    • Cerebrovascular and genetic disorders 3

Sara Nava

29 papers receiving 875 citations

Peers

Sara Nava
Comparison fields: 5 of 84
  • Genetics 216
  • Oncology 342
  • Immunology 264
  • Developmental Neuroscience 40
  • Neurology 74
Replace Piotr Rieske with:
Piotr Rieske Poland
Kam Sze Tsang Hong Kong
Federica Servida Italy
Yongzheng He United States
Dorota Jesionek‐Kupnicka Poland
Ken Samoto Japan
Kenichi Miharada Japan
Yasushi Adachi Japan
Alison Z. Young United States
Gabryella S. P. Santos Brazil
Sara Nava relative to Piotr Rieske Poland Piotr Rieske's profile →
Citations per field
00.5×3.3×
Piotr Rieske · 1×
Citations per year

Countries citing papers authored by Sara Nava

Since Specialization
Citations

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

Fields of papers citing papers by Sara Nava

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006203
2 200593
3 201369
4 201353
5 201945
6 201642
7 200739
8 202136
9 201231
10 201726
11 201324
12 201124
13 200823
14 201022
15 202022
16 201520
17 202319
18 202117
19 201917
20 201816

About Sara Nava

Sara Nava is a scholar working on Oncology, Neurology, Molecular Biology, Immunology and Genetics, having authored 29 papers that have together received 894 indexed citations. Recurring topics across this work include Mesenchymal stem cell research (7 papers), CAR-T cell therapy research (7 papers), Immunotherapy and Immune Responses (6 papers), Cancer Cells and Metastasis (5 papers), Moyamoya disease diagnosis and treatment (4 papers), Tissue Engineering and Regenerative Medicine (3 papers), RNA Interference and Gene Delivery (3 papers) and Cerebrovascular and genetic disorders (3 papers). The work is most often cited by research in Genetics (216 citations), Oncology (342 citations), Immunology (264 citations), Developmental Neuroscience (40 citations) and Neurology (74 citations). Sara Nava has collaborated with scholars based in Italy, United Kingdom and United States. Frequent co-authors include Eugenio Parati, Simona Frigerio, Serena Pellegatta, Gaetano Finocchiaro, Maria Grazia Bruzzone, Fulvio Baggi, Anna Bersano, Pietro Luigi Poliani, Blanca Suárez-Merino and Maria Ravanini. Their work appears in journals such as International Journal of Molecular Sciences, Pharmaceutics, Journal of Neuroimmunology, The Journal of Immunology and PLoS ONE.

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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