Giulia Perrone

4.1k total citations
53 papers, 2.4k citations indexed

About

Giulia Perrone is a scholar working on Hematology, Molecular Biology and Oncology. According to data from OpenAlex, Giulia Perrone has authored 53 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Hematology, 30 papers in Molecular Biology and 26 papers in Oncology. Recurrent topics in Giulia Perrone's work include Multiple Myeloma Research and Treatments (35 papers), Protein Degradation and Inhibitors (13 papers) and Cancer Treatment and Pharmacology (10 papers). Giulia Perrone is often cited by papers focused on Multiple Myeloma Research and Treatments (35 papers), Protein Degradation and Inhibitors (13 papers) and Cancer Treatment and Pharmacology (10 papers). Giulia Perrone collaborates with scholars based in Italy, United States and Japan. Giulia Perrone's co-authors include Michèle Cavo, Michele Baccarani, Elena Zamagni, Paola Tacchetti, Patrizia Tosi, Teru Hideshima, Güllü Görgün, Noopur Raje, Annamaria Brioli and Delia Cangini and has published in prestigious journals such as Journal of Clinical Oncology, Blood and Cancer Research.

In The Last Decade

Giulia Perrone

52 papers receiving 2.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Giulia Perrone Italy 20 1.5k 1.3k 1.2k 267 248 53 2.4k
Diana Cirstea United States 22 894 0.6× 1.6k 1.3× 1.1k 0.9× 188 0.7× 168 0.7× 80 2.4k
Dixie Esseltine United States 22 1.9k 1.2× 1.8k 1.4× 1.6k 1.4× 230 0.9× 539 2.2× 44 3.1k
Merav Leiba Israel 23 929 0.6× 824 0.6× 930 0.8× 586 2.2× 224 0.9× 77 2.0k
Sheeba K. Thomas United States 24 1.1k 0.8× 1.1k 0.8× 889 0.8× 249 0.9× 366 1.5× 161 2.0k
Lugui Qiu China 27 1.4k 0.9× 1.5k 1.1× 1.3k 1.1× 494 1.9× 503 2.0× 255 2.9k
Dario Ferrero Italy 25 1.0k 0.7× 872 0.7× 472 0.4× 338 1.3× 488 2.0× 92 2.0k
Ivan Špıčka Czechia 24 3.1k 2.1× 2.4k 1.8× 2.1k 1.8× 249 0.9× 474 1.9× 141 3.7k
María Teresa Cibeira Spain 23 1.3k 0.8× 1.3k 1.0× 709 0.6× 182 0.7× 398 1.6× 91 2.0k
Steven Novick United States 16 645 0.4× 819 0.6× 437 0.4× 142 0.5× 362 1.5× 28 1.4k
Gabriel Ghiaur United States 25 725 0.5× 934 0.7× 479 0.4× 413 1.5× 230 0.9× 87 1.9k

Countries citing papers authored by Giulia Perrone

Since Specialization
Citations

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

Fields of papers citing papers by Giulia Perrone

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Giulia Perrone

This figure shows the co-authorship network connecting the top 25 collaborators of Giulia Perrone. A scholar is included among the top collaborators of Giulia Perrone 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 Giulia Perrone. Giulia Perrone 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
1.
Montefusco, Vittorio, Mónica Galli, Francesco Spina, et al.. (2014). Autoimmune diseases during treatment with immunomodulatory drugs in multiple myeloma: selective occurrence after lenalidomide. Leukemia & lymphoma. 55(9). 2032–2037. 16 indexed citations
2.
Borsi, Enrica, Giulia Perrone, Carolina Terragna, et al.. (2014). HIF-1α inhibition blocks the cross talk between multiple myeloma plasma cells and tumor microenvironment. Experimental Cell Research. 328(2). 444–455. 24 indexed citations
3.
Perrone, Giulia, Lucia Farina, & Paolo Corradini. (2013). Current state of art for transplantation paradigms in peripheral T-cell lymphomas. Expert Review of Hematology. 6(4). 465–474. 2 indexed citations
4.
Pantani, Lucia, Elena Zamagni, Beatrice Anna Zannetti, et al.. (2013). Bortezomib and dexamethasone as salvage therapy in patients with relapsed/refractory multiple myeloma: analysis of long-term clinical outcomes. Annals of Hematology. 93(1). 123–128. 12 indexed citations
5.
Perrone, Giulia & Paolo Corradini. (2013). Autologous Stem Cell Transplantation for T-Cell Lymphomas. Seminars in Hematology. 51(1). 59–66. 13 indexed citations
6.
Nanni, Cristina, Elena Zamagni, Monica Celli, et al.. (2012). The Value of 18F-FDG PET/CT after Autologous Stem Cell Transplantation (ASCT) in Patients Affected by Multiple Myeloma (MM). Clinical Nuclear Medicine. 38(2). e74–e79. 51 indexed citations
7.
Zamagni, Elena, Patrizia Tosi, Paola Tacchetti, et al.. (2011). Long-term results of thalidomide and dexamethasone (thal–dex) as therapy of first relapse in multiple myeloma. Annals of Hematology. 91(3). 419–426. 10 indexed citations
8.
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Perrone, Giulia, Enrica Borsi, Carolina Terragna, et al.. (2011). HIF 1 Alpha: A Suitable Target for Multiple Myeloma. Blood. 118(21). 2901–2901. 1 indexed citations
10.
Cirstea, Diana, Teru Hideshima, Scott J. Rodig, et al.. (2010). Dual Inhibition of Akt/Mammalian Target of Rapamycin Pathway by Nanoparticle Albumin-Bound –Rapamycin and Perifosine Induces Antitumor Activity in Multiple Myeloma. Molecular Cancer Therapeutics. 9(4). 963–975. 136 indexed citations
11.
Ikeda, Hiroshi, Teru Hideshima, Mariateresa Fulciniti, et al.. (2010). PI3K/p110δ is a novel therapeutic target in multiple myeloma. Blood. 116(9). 1460–1468. 156 indexed citations
12.
Santo, Loredana, Sonia Vallet, Teru Hideshima, et al.. (2010). AT7519, A novel small molecule multi-cyclin-dependent kinase inhibitor, induces apoptosis in multiple myeloma via GSK-3β activation and RNA polymerase II inhibition. Oncogene. 29(16). 2325–2336. 114 indexed citations
13.
Tosi, Patrizia, Elena Zamagni, Paola Tacchetti, et al.. (2010). Thalidomide-Dexamethasone as Induction Therapy before Autologous Stem Cell Transplantation in Patients with Newly Diagnosed Multiple Myeloma and Renal Insufficiency. Biology of Blood and Marrow Transplantation. 16(8). 1115–1121. 26 indexed citations
14.
Perrone, Giulia, Teru Hideshima, Hiroshi Ikeda, et al.. (2009). Ascorbic acid inhibits antitumor activity of bortezomib in vivo. Leukemia. 23(9). 1679–1686. 79 indexed citations
15.
Tosi, Patrizia, Carolina Terragna, Nicoletta Testoni, et al.. (2007). Evaluation of bone disease in multiple myeloma patients carrying the t(4;14) chromosomal translocation. European Journal Of Haematology. 80(1). 31–36. 3 indexed citations
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Tosi, Patrizia, Elena Zamagni, Claudia Cellini, et al.. (2005). Neurological toxicity of long‐term (>1 yr) thalidomide therapy in patients with multiple myeloma. European Journal Of Haematology. 74(3). 212–216. 74 indexed citations
19.
Cavo, Michèle, Paola Tacchetti, Elena Zamagni, et al.. (2004). Superiority of First-Line Thalidomide-Dexamethasone over Vincristine-Doxorubicin-Dexamethasone in Preparation for Autologous Stem Cell Transplantation for Multiple Myeloma.. Blood. 104(11). 1489–1489. 12 indexed citations
20.
Arpinati, Mario, Gabriella Chirumbolo, Benedetta Urbini, et al.. (2003). Role of plasmacytoid dendritic cells in immunity and tolerance after allogeneic hematopoietic stem cell transplantation. Transplant Immunology. 11(3-4). 345–356. 54 indexed citations

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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