Marco Andreani

6.1k total citations · 1 hit paper
213 papers, 4.1k citations indexed

About

Marco Andreani is a scholar working on Immunology, Hematology and Genetics. According to data from OpenAlex, Marco Andreani has authored 213 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 150 papers in Immunology, 63 papers in Hematology and 37 papers in Genetics. Recurrent topics in Marco Andreani's work include T-cell and B-cell Immunology (130 papers), Immune Cell Function and Interaction (126 papers) and Hematopoietic Stem Cell Transplantation (54 papers). Marco Andreani is often cited by papers focused on T-cell and B-cell Immunology (130 papers), Immune Cell Function and Interaction (126 papers) and Hematopoietic Stem Cell Transplantation (54 papers). Marco Andreani collaborates with scholars based in Italy, France and United States. Marco Andreani's co-authors include Giuseppe Lucarelli, Emanuele Angelucci, Guido Lucarelli, S Nesci, Javid Gaziev, F Agostinelli, Pietro Sodani, M Galimberti, Claudio Giardini and D Baronciani and has published in prestigious journals such as New England Journal of Medicine, Nature Medicine and SHILAP Revista de lepidopterología.

In The Last Decade

Marco Andreani

194 papers receiving 4.0k citations

Hit Papers

Coexpression of CD49b and LAG-3 identifies human and mous... 2013 2026 2017 2021 2013 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marco Andreani Italy 32 1.8k 1.7k 1.4k 784 542 213 4.1k
Hélène Espérou France 36 2.9k 1.6× 1.0k 0.6× 1.1k 0.8× 700 0.9× 743 1.4× 90 4.6k
Masahiro Tsuchida Japan 34 2.9k 1.7× 944 0.5× 527 0.4× 503 0.6× 736 1.4× 160 4.3k
Leo Luznik United States 41 4.4k 2.5× 2.8k 1.6× 858 0.6× 487 0.6× 433 0.8× 129 5.6k
Mitchell E. Horwitz United States 31 2.5k 1.4× 1.3k 0.8× 483 0.3× 257 0.3× 726 1.3× 144 3.8k
Voravit Ratanatharathorn United States 29 2.0k 1.1× 1.1k 0.6× 369 0.3× 293 0.4× 350 0.6× 140 3.6k
Lee Ann Baxter‐Lowe United States 28 1.9k 1.1× 1.7k 1.0× 341 0.2× 232 0.3× 296 0.5× 90 3.2k
NS Young United States 33 2.0k 1.1× 1.3k 0.7× 640 0.5× 373 0.5× 790 1.5× 80 4.4k
JA Hansen United States 30 3.4k 1.9× 1.7k 1.0× 780 0.6× 354 0.5× 335 0.6× 67 4.3k
Pablo Rubinstein United States 25 2.7k 1.5× 1.8k 1.1× 1.2k 0.8× 384 0.5× 968 1.8× 61 4.9k
Yoshihisa Kodera Japan 34 2.6k 1.4× 1.8k 1.1× 483 0.3× 203 0.3× 584 1.1× 143 4.1k

Countries citing papers authored by Marco Andreani

Since Specialization
Citations

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

Fields of papers citing papers by Marco Andreani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marco Andreani

This figure shows the co-authorship network connecting the top 25 collaborators of Marco Andreani. A scholar is included among the top collaborators of Marco Andreani 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 Andreani. Marco Andreani 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.
Cargou, Marine, et al.. (2025). Characterisation of the Novel HLA‐DQA1*01:170 by Sequencing‐Based Typing. HLA. 105(4). e70185–e70185.
2.
Cargou, Marine, et al.. (2025). Characterisation of the Novel HLA‐DQA1*01:169 Allele by Sequencing‐Based Typing. HLA. 105(4). e70184–e70184.
3.
Galluccio, Tiziana, et al.. (2025). Identification of the Novel Allele, HLA‐DQB1*03:577 , by Next‐Generation Sequencing. HLA. 106(5). e70468–e70468.
4.
Troiano, Maria, et al.. (2025). Characterisation of the Novel HLA‐B*08:01:80 Allele Identified by Next‐Generation Sequencing. HLA. 106(6). e70470–e70470.
5.
Cargou, Marine, et al.. (2025). Characterisation of the Novel HLA‐DQA1*01:67:02 Allele by Sequencing‐Based Typing. HLA. 105(2). e70084–e70084. 1 indexed citations
6.
Cargou, Marine, Marco Andreani, Tiziana Galluccio, Mamy Ralazamahaleo, & Jonathan Visentin. (2024). Characterisation of the novel HLA‐DQA1*01:02:24 allele by sequencing‐based typing. HLA. 104(3). e15671–e15671. 2 indexed citations
7.
Andreani, Marco, Feliciana Mariotti, Franco Locatelli, et al.. (2024). HLA alleles associated to susceptibility to gliptin‐associated bullous pemphigoid in Italian patients. HLA. 104(2). e15616–e15616. 2 indexed citations
8.
Cargou, Marine, et al.. (2024). Characterisation of the novel HLA‐DRB4*01:01:12 allele by sequencing‐based typing. HLA. 103(5). e15538–e15538. 1 indexed citations
9.
Galluccio, Tiziana, et al.. (2024). Identification of the novel HLA‐A*30:221 allele by next‐generation sequencing. HLA. 104(1). e15592–e15592. 2 indexed citations
10.
Cargou, Marine, et al.. (2024). Characterisation of the novel HLA‐DPA1*01:12:03 allele by sequencing‐based typing. HLA. 104(3). e15674–e15674. 2 indexed citations
11.
Cargou, Marine, et al.. (2023). Characterization of the novel HLA‐DPA1*01:150 allele by sequencing‐based typing. HLA. 102(4). 543–545. 2 indexed citations
12.
Cargou, Marine, et al.. (2023). Characterization of the novel HLA‐DRB3*02:192 allele by sequencing‐based typing. HLA. 102(5). 640–641. 2 indexed citations
13.
Merli, Pietro, Daria Pagliara, Federica Galaverna, et al.. (2021). TCRαβ/CD19 depleted HSCT from an HLA-haploidentical relative to treat children with different nonmalignant disorders. Blood Advances. 6(1). 281–292. 25 indexed citations
14.
Strocchio, Luisa, Daria Pagliara, Mattia Algeri, et al.. (2021). HLA-haploidentical TCRαβ+/CD19+-depleted stem cell transplantation in children and young adults with Fanconi anemia. Blood Advances. 5(5). 1333–1339. 15 indexed citations
15.
Gaziev, Javid, Simone Marziali, Katia Paciaroni, et al.. (2017). Posterior Reversible Encephalopathy Syndrome after Hematopoietic Cell Transplantation in Children with Hemoglobinopathies. Biology of Blood and Marrow Transplantation. 23(9). 1531–1540. 43 indexed citations
16.
Cifaldi, Loredana, Paolo Romania, Michela Falco, et al.. (2015). ERAP1 Regulates Natural Killer Cell Function by Controlling the Engagement of Inhibitory Receptors. Cancer Research. 75(5). 824–834. 53 indexed citations
17.
Perrone, Maria Paola, et al.. (2012). Identification of a novel HLA‐DPB1 allele, DPB1*138:01, by sequence‐based typing. Tissue Antigens. 80(2). 195–196. 4 indexed citations
18.
Serafini, Gianluca, Marco Andreani, M. Testi, et al.. (2009). Type 1 regulatory T cells are associated with persistent split erythroid/lymphoid chimerism after allogeneic hematopoietic stem cell transplantation for thalassemia. Haematologica. 94(10). 1415–1426. 45 indexed citations
19.
Gaziev, Javid, M Galimberti, Giuseppe Lucarelli, et al.. (2000). Bone marrow transplantation from alternative donors for thalassemia: HLA-phenotypically identical relative and HLA-nonidentical sibling or parent transplants. Bone Marrow Transplantation. 25(8). 815–821. 95 indexed citations
20.
Nesci, S, et al.. (1992). Mixed chimerism in thalassemic patients after bone marrow transplantation.. PubMed. 10(2). 143–6. 52 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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