Roberto Mina

3.1k citations
52 papers · 682 · h-index 15

Impact in

  • Hematology top 2%
    • Multiple Myeloma Research and Treatments
  • Oncology top 10%
    • Peptidase Inhibition and Analysis
    • CAR-T cell therapy research
    • Cancer Treatment and Pharmacology

Papers in

    • Multiple Myeloma Research and Treatments 45
    • Chronic Myeloid Leukemia Treatments 3
    • Peptidase Inhibition and Analysis 14
    • Cancer Treatment and Pharmacology 8
    • CAR-T cell therapy research 4

Roberto Mina

47 papers receiving 669 citations

Peers

Roberto Mina
Comparison fields: 5 of 48
  • Hematology 532
  • Oncology 311
  • Genetics 69
  • Molecular Biology 410
  • Geriatrics and Gerontology 7
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Roberto Mina relative to Nisha S. Joseph United States Nisha S. Joseph's profile →
Citations per field
00.5×2×2.9×
Nisha S. Joseph · 1×
Citations per year

Countries citing papers authored by Roberto Mina

Since Specialization
Citations

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

Fields of papers citing papers by Roberto Mina

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201367
2 201360
3 201947
4 201938
5 201938
6 201737
7 201835
8 201834
9 201631
10 202327
11 201919
12 201919
13 202119
14 202217
15 201314
16 202014
17 202414
18 202313
19 201513
20 202212

About Roberto Mina

Roberto Mina is a scholar working on Hematology, Oncology, Molecular Biology, Genetics and Radiology, Nuclear Medicine and Imaging, having authored 52 papers that have together received 682 indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (45 papers), Protein Degradation and Inhibitors (16 papers), Peptidase Inhibition and Analysis (14 papers), Cancer Treatment and Pharmacology (8 papers), Chronic Lymphocytic Leukemia Research (6 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (4 papers), CAR-T cell therapy research (4 papers) and Chronic Myeloid Leukemia Treatments (3 papers). The work is most often cited by research in Hematology (532 citations), Oncology (311 citations), Genetics (69 citations), Molecular Biology (410 citations) and Geriatrics and Gerontology (7 citations). Roberto Mina has collaborated with scholars based in Italy, United States and Netherlands. Frequent co-authors include Antonio Palumbo, Francesca Gay, Mario Boccadoro, Sara Bringhen, Sagar Lonial, Alessandra Larocca, Francesca Bonello, Chiara Cerrato, Mattia D’Agostino and Stefania Oliva. Their work appears in journals such as Blood, Journal of Clinical Oncology, The Lancet Haematology, HemaSphere and Frontiers in Oncology.

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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