Marco Della Peruta

2.4k total citations
20 papers, 843 citations indexed

About

Marco Della Peruta is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Marco Della Peruta has authored 20 papers receiving a total of 843 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 7 papers in Oncology and 6 papers in Immunology. Recurrent topics in Marco Della Peruta's work include CAR-T cell therapy research (5 papers), Protein Tyrosine Phosphatases (5 papers) and Virus-based gene therapy research (3 papers). Marco Della Peruta is often cited by papers focused on CAR-T cell therapy research (5 papers), Protein Tyrosine Phosphatases (5 papers) and Virus-based gene therapy research (3 papers). Marco Della Peruta collaborates with scholars based in Italy, United Kingdom and United States. Marco Della Peruta's co-authors include Aldo Scarpa, Claudio Sorio, Stefania Beghelli, Gianfranco Delle Fave, Paolo Pederzoli, Stefano Barbi, Lorenzo Piemonti, Alessia Di Florio, Gabriele Capurso and Irene Dalai and has published in prestigious journals such as The Lancet, Journal of Clinical Oncology and Blood.

In The Last Decade

Marco Della Peruta

19 papers receiving 831 citations

Peers

Marco Della Peruta
Comparison fields: 5 of 78
  • Oncology 430
  • Molecular Biology 383
  • Epidemiology 366
  • Neurology 184
  • Genetics 84
Replace Shinji Kudoh with:
Shinji Kudoh Japan
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Géraldine Farjot France
Carolin Schmidt Germany
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Rutger Meinsma Netherlands
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Yeon‐Tae Jeong South Korea
Marie Morfouace France
Richard Karlsson Denmark
Shinji Kudoh Japan View profile →
Citations per field, relative to Marco Della Peruta
Marco Della Peruta · 1×
Citations per year, relative to Marco Della Peruta
Marco Della Peruta · 1×

Countries citing papers authored by Marco Della Peruta

Since Specialization
Citations

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

Fields of papers citing papers by Marco Della Peruta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marco Della Peruta. 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 Marco Della Peruta. The network helps show where Marco Della Peruta may publish in the future.

Co-authorship network of co-authors of Marco Della Peruta

This figure shows the co-authorship network connecting the top 25 collaborators of Marco Della Peruta. A scholar is included among the top collaborators of Marco Della Peruta based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Marco Della Peruta. Marco Della Peruta is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 24
3 1
4 7
5 39
6 13
7 3
8 29
9 35
10 40
11 44
12 15
13 7
14
Protein tyrosine phosphatase receptor type gamma (PTPRG) is a functional tumor suppressor gene specifically down-regulated in chronic myeloid leukemia (CML)
1
15 417
16 20
17 26
18
Protein Tyrosine Phosphatase Gamma (PTPgamma) is a Novel Leukocyte Marker Highly Expressed by CD34 Precursors.
9
19 10
20 103

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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