Bruno Paiva
Impact in
- Hematology top 0.1%
- Multiple Myeloma Research and Treatments
- Genetics top 1%
- Chronic Lymphocytic Leukemia Research
Papers in
- Hematology 126
- Multiple Myeloma Research and Treatments 118
-
- Protein Degradation and Inhibitors 44
- Co-authors
- Jesús F. San Miguel (91 shared papers)Alberto Órfão (23 shared papers)Jacques J. M. van Dongen (14 shared papers)María‐Victoria Mateos (40 shared papers)María‐Belén Vídriales (22 shared papers)Felipe Prósper (31 shared papers)Juan José Lahuerta (28 shared papers)Martín Pérez‐Andrés (10 shared papers)
- Journals
- Blood (57 papers)Haematologica (12 papers)Cancers (7 papers)Cytometry Part B Clinical Cytometry (7 papers)Journal of Clinical Oncology (6 papers)
- Partner nations
- SpainUnited StatesGermany
In The Last Decade
Bruno Paiva
146 papers receiving 4.6k citations
Peers
Comparison fields: 5 of 110
- Hematology 3.4k
- Genetics 829
- Oncology 1.9k
- Molecular Biology 2.6k
- Immunology 804
Countries citing papers authored by Bruno Paiva
This map shows the geographic impact of Bruno Paiva'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 Bruno Paiva with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bruno Paiva more than expected).
Fields of papers citing papers by Bruno Paiva
This network shows the impact of papers produced by Bruno Paiva. 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 Bruno Paiva. The network helps show where Bruno Paiva may publish in the future.
Co-authors
The 25 scholars most cited alongside Bruno Paiva, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 157 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 348 | |
| 2 | 2020 | 226 | |
| 3 | 2010 | 203 | |
| 4 | 2015 | 195 | |
| 5 | 2010 | 185 | |
| 6 | 2011 | 157 | |
| 7 | 2018 | 152 | |
| 8 | 2019 | 148 | |
| 9 | 2015 | 148 | |
| 10 | 2010 | 137 | |
| 11 | 2012 | 125 | |
| 12 | 2013 | 115 | |
| 13 | 2015 | 113 | |
| 14 | 2016 | 107 | |
| 15 | 2011 | 103 | |
| 16 | 2021 | 92 | |
| 17 | 2018 | 90 | |
| 18 | 2015 | 84 | |
| 19 | 2019 | 83 | |
| 20 | 2021 | 78 |
About Bruno Paiva
Bruno Paiva is a scholar working on Hematology, Molecular Biology, Oncology, Immunology and Genetics, having authored 157 papers that have together received 4.7k indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (118 papers), Protein Degradation and Inhibitors (44 papers), Peptidase Inhibition and Analysis (27 papers), Chronic Lymphocytic Leukemia Research (19 papers), CAR-T cell therapy research (18 papers), Chemokine receptors and signaling (15 papers), Monoclonal and Polyclonal Antibodies Research (13 papers) and Immune Cell Function and Interaction (11 papers). The work is most often cited by research in Hematology (3.4k citations), Genetics (829 citations), Oncology (1.9k citations), Molecular Biology (2.6k citations) and Immunology (804 citations). Bruno Paiva has collaborated with scholars based in Spain, United States and Germany. Frequent co-authors include Jesús F. San Miguel, Alberto Órfão, Jacques J. M. van Dongen, María‐Victoria Mateos, María‐Belén Vídriales, Felipe Prósper, Juan José Lahuerta, Martín Pérez‐Andrés, Ramón García‐Sánz and Paula Rodríguez‐Otero. Their work appears in journals such as Blood, Haematologica, Cancers, Cytometry Part B Clinical Cytometry 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.