Giulia Fabbri

36 papers receiving 2.6k citations

Giulia Fabbri's Hit Papers

Analysis of the coding genome of diffuse large B-cell lymphoma 2011 · 673 citations
6730+5+10Years since publication200400600

Peers

Giulia Fabbri
Comparison fields: 5 of 104
  • Genetics 831
  • Pathology and Forensic Medicine 1.1k
  • Cancer Research 605
  • Hematology 314
  • Immunology 488
Replace Tony G. Willis with:
Tony G. Willis United Kingdom
Magda Pinyol Spain
Monica Messina Italy
Stefan Gesk Germany
Clelia Tiziana Storlazzi Italy
Francine Mugneret France
Karen Pulford United Kingdom
Masashi Sanada Japan
Mara Compagno Italy
Andreas Bühler Germany
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Countries citing papers authored by Giulia Fabbri

Since Specialization
Citations

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

Fields of papers citing papers by Giulia Fabbri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Analysis of the coding genome of diffuse large B-cell lymphoma
Hit paper breakdown →
2011673
2
Inactivating mutations of acetyltransferase genes in B-cell lymphoma
Hit paper breakdown →
2011644
3 2014340
4 2013198
5 2016187
6 201791
7 202070
8 200857
9 201454
10 201954
11 201453
12 202141
13 201728
14 202323
15 202123
16 201422
17 201917
18 202212
19 201710
20
Optimization and robustness of complex material model simulations with modeFRONTIER
20096

About Giulia Fabbri

Giulia Fabbri is a scholar working on Molecular Biology, Oncology, Cancer Research, Genetics and Sociology and Political Science, having authored 43 papers that have together received 2.6k indexed citations. Recurring topics across this work include Chronic Lymphocytic Leukemia Research (7 papers), Italian Fascism and Post-war Society (5 papers), Cancer Genomics and Diagnostics (4 papers), Genetic and phenotypic traits in livestock (3 papers), Microtubule and mitosis dynamics (3 papers), Genetic diversity and population structure (3 papers), Lymphoma Diagnosis and Treatment (3 papers) and Cancer-related Molecular Pathways (3 papers). The work is most often cited by research in Genetics (831 citations), Pathology and Forensic Medicine (1.1k citations), Cancer Research (605 citations), Hematology (314 citations) and Immunology (488 citations). Giulia Fabbri has collaborated with scholars based in Italy, United States and United Kingdom. Frequent co-authors include Riccardo Dalla‐Favera, Raúl Rabadán, Laura Pasqualucci, Charles G. Mullighan, Davide Rossi, Gianluca Gaïdano, Amy Chadburn, Adina Grunn, Jing Ma and Annalisa Chiarenza. Their work appears in journals such as Blood, Journal of Postcolonial Writing, Cancer Research, International Journal of Molecular Sciences and Journal of Clinical 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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