Marina Martello

826 total citations
30 papers, 472 citations indexed

About

Marina Martello is a scholar working on Molecular Biology, Hematology and Oncology. According to data from OpenAlex, Marina Martello has authored 30 papers receiving a total of 472 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 21 papers in Hematology and 12 papers in Oncology. Recurrent topics in Marina Martello's work include Multiple Myeloma Research and Treatments (21 papers), Protein Degradation and Inhibitors (12 papers) and Peptidase Inhibition and Analysis (7 papers). Marina Martello is often cited by papers focused on Multiple Myeloma Research and Treatments (21 papers), Protein Degradation and Inhibitors (12 papers) and Peptidase Inhibition and Analysis (7 papers). Marina Martello collaborates with scholars based in Italy, Greece and United States. Marina Martello's co-authors include Carolina Terragna, Michèle Cavo, Paola Tacchetti, Enrica Borsi, Annamaria Brioli, Elena Zamagni, Lucia Pantani, Serena Rocchi, Beatrice Anna Zannetti and Katia Mancuso and has published in prestigious journals such as Nature Communications, Blood and Clinical Cancer Research.

In The Last Decade

Marina Martello

28 papers receiving 466 citations

Peers

Marina Martello
Enrica Borsi Italy
Norbert Grząśko Poland
Daniele Derudas Italy
Roberto Mina Italy
Weiwei Sui China
Annemiek Broijl Netherlands
Jean Emmanuel Sarry France
Kathleen Kelly United States
Claudia E. Paba‐Prada United States
P. Dieringer United States
Enrica Borsi Italy
Marina Martello
Citations per year, relative to Marina Martello Marina Martello (= 1×) peers Enrica Borsi

Countries citing papers authored by Marina Martello

Since Specialization
Citations

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

Fields of papers citing papers by Marina Martello

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marina Martello

This figure shows the co-authorship network connecting the top 25 collaborators of Marina Martello. A scholar is included among the top collaborators of Marina Martello 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 Marina Martello. Marina Martello 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.
D’Agostino, Mattia, Marina Martello, Lorenzo De Paoli, et al.. (2025). Overview of 1q abnormalities in multiple myeloma: scientific opinions from Italian experts. Annals of Hematology. 104(3). 1443–1458. 1 indexed citations
2.
Terragna, Carolina, Marina Martello, Elena Zamagni, et al.. (2024). Multi-dimensional scaling techniques unveiled gain1q&loss13q co-occurrence in Multiple Myeloma patients with specific genomic, transcriptional and adverse clinical features. Nature Communications. 15(1). 1551–1551. 5 indexed citations
3.
Borsi, Enrica, Marina Martello, Elena Zamagni, et al.. (2023). High levels of CRBN isoform lacking IMiDs binding domain predicts for a worse response to IMiDs-based upfront therapy in newly diagnosed myeloma patients. Clinical and Experimental Medicine. 23(8). 5227–5239. 4 indexed citations
4.
Martello, Marina, Enrica Borsi, Luca Dozza, et al.. (2022). Clonal and subclonal TP53 molecular impairment is associated with prognosis and progression in multiple myeloma. Blood Cancer Journal. 12(1). 15–15. 17 indexed citations
5.
Borsi, Enrica, et al.. (2022). : A copy number clustering tool designed to refit and recalibrate the baseline region of tumors’ profiles. Computational and Structural Biotechnology Journal. 20. 3718–3728. 1 indexed citations
6.
Broccoli, Alessandro, Carolina Terragna, Marina Martello, et al.. (2021). Droplet digital polymerase chain reaction for the assessment of disease burden in hairy cell leukemia. Hematological Oncology. 40(1). 58–63. 9 indexed citations
7.
Forte, Dorian, Flaminia Fanelli, Marco Mezzullo, et al.. (2020). Disease-Specific Derangement of Circulating Endocannabinoids and N-Acylethanolamines in Myeloproliferative Neoplasms. International Journal of Molecular Sciences. 21(9). 3399–3399. 5 indexed citations
8.
Ziccheddu, Bachisio, Giulia Biancon, Chiara De Philippis, et al.. (2020). Integrative analysis of the genomic and transcriptomic landscape of double-refractory multiple myeloma. Blood Advances. 4(5). 830–844. 49 indexed citations
9.
Martello, Marina. (2020). Usefulness of Circulating Cell-Free DNA to Define and Tracking How Multiple Myeloma Spread and Disseminate Outside the Bone Marrow.
10.
Mancuso, Katia, Paola Tacchetti, Lucia Pantani, et al.. (2020). Maintenance therapy with bortezomib and dexamethasone after autotransplantation for high-risk multiple myeloma. Bone Marrow Transplantation. 55(9). 1865–1867. 1 indexed citations
11.
Romano, Alessandra, Giuseppe A. Palumbo, Nunziatina Laura Parrinello, et al.. (2019). Minimal Residual Disease Assessment Within the Bone Marrow of Multiple Myeloma: A Review of Caveats, Clinical Significance and Future Perspectives. Frontiers in Oncology. 9. 699–699. 40 indexed citations
12.
Zannetti, Beatrice Anna, Paola Tacchetti, Lucia Pantani, et al.. (2017). Novel agent-based salvage autologous stem cell transplantation for relapsed multiple myeloma. Annals of Hematology. 96(12). 2071–2078. 3 indexed citations
13.
Martello, Marina, Daniel Remondini, Enrica Borsi, et al.. (2016). Opposite activation of the Hedgehog pathway in CD138+ plasma cells and CD138−CD19+ B cells identifies two subgroups of patients with multiple myeloma and different prognosis. Leukemia. 30(9). 1869–1876. 9 indexed citations
14.
Terragna, Carolina, Marina Martello, Lucia Pantani, et al.. (2016). A Branching Evolution Model at Relapse Characterizes Multiple Myeloma Patients Who Responded to up-Front Combination Therapy Including New Drugs. Blood. 128(22). 2080–2080. 1 indexed citations
15.
Zamagni, Elena, Cristina Nanni, Katia Mancuso, et al.. (2015). PET/CT Improves the Definition of Complete Response and Allows to Detect Otherwise Unidentifiable Skeletal Progression in Multiple Myeloma. Clinical Cancer Research. 21(19). 4384–4390. 107 indexed citations
16.
Pantani, Lucia, Annamaria Brioli, Paola Tacchetti, et al.. (2015). Current and emerging triplet combination therapies for relapsed and refractory multiple myeloma. Expert Review of Hematology. 9(3). 315–323. 4 indexed citations
17.
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
18.
Borsi, Enrica, Carolina Terragna, Annamaria Brioli, et al.. (2014). Therapeutic targeting of hypoxia and hypoxia-inducible factor 1 alpha in multiple myeloma. Translational research. 165(6). 641–650. 50 indexed citations
19.
20.
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

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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