Robert Redd
Impact in
- Pathology and Forensic Medicine top 0.5%
- Lymphoma Diagnosis and Treatment
- Hematology top 1%
- Acute Myeloid Leukemia Research
Papers in
- Oncology 46
- CAR-T cell therapy research 23
- Cancer Immunotherapy and Biomarkers 8
-
- Lymphoma Diagnosis and Treatment 34
- Co-authors
- Donna Neuberg (34 shared papers)Scott J. Rodig (13 shared papers)Margaret A. Shipp (13 shared papers)Philippe Armand (26 shared papers)Bjoern Chapuy (7 shared papers)Azra H. Ligon (4 shared papers)Gordon J. Freeman (2 shared papers)Richard T. Hoppe (3 shared papers)
- Journals
- Blood (39 papers)Journal of Clinical Oncology (9 papers)Blood Advances (8 papers)British Journal of Haematology (2 papers)Hematological Oncology (2 papers)
- Partner nations
- United StatesNetherlandsGermany
In The Last Decade
Robert Redd
100 papers receiving 2.9k citations
Robert Redd's Hit Papers
Peers
Comparison fields: 5 of 86
- Pathology and Forensic Medicine 1.2k
- Hematology 684
- Genetics 597
- Oncology 1.4k
- Immunology 818
Countries citing papers authored by Robert Redd
This map shows the geographic impact of Robert Redd'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 Robert Redd with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert Redd more than expected).
Fields of papers citing papers by Robert Redd
This network shows the impact of papers produced by Robert Redd. 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 Robert Redd. The network helps show where Robert Redd may publish in the future.
Co-authors
The 25 scholars most cited alongside Robert Redd, 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 106 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | PD-L1 and PD-L2 Genetic Alterations Define Classical Hodgkin Lymphoma and Predict Outcome Hit paper breakdown → | 2016 | 574 |
| 2 | Prognostic Mutations in Myelodysplastic Syndrome after Stem-Cell Transplantation Hit paper breakdown → | 2017 | 491 |
| 3 | 2017 | 227 | |
| 4 | 2019 | 170 | |
| 5 | 2016 | 142 | |
| 6 | 2018 | 120 | |
| 7 | 2018 | 95 | |
| 8 | 2020 | 94 | |
| 9 | 2019 | 82 | |
| 10 | 2019 | 64 | |
| 11 | 2015 | 59 | |
| 12 | 2016 | 50 | |
| 13 | 2014 | 46 | |
| 14 | 2016 | 37 | |
| 15 | 2020 | 33 | |
| 16 | 2016 | 31 | |
| 17 | 2019 | 30 | |
| 18 | 2015 | 27 | |
| 19 | 2017 | 26 | |
| 20 | 2021 | 26 |
About Robert Redd
Robert Redd is a scholar working on Oncology, Pathology and Forensic Medicine, Genetics, Hematology and Molecular Biology, having authored 106 papers that have together received 2.9k indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (34 papers), CAR-T cell therapy research (23 papers), Chronic Lymphocytic Leukemia Research (22 papers), Multiple Myeloma Research and Treatments (16 papers), Acute Myeloid Leukemia Research (10 papers), Cancer Genomics and Diagnostics (8 papers), Protein Degradation and Inhibitors (8 papers) and Cancer Immunotherapy and Biomarkers (8 papers). The work is most often cited by research in Pathology and Forensic Medicine (1.2k citations), Hematology (684 citations), Genetics (597 citations), Oncology (1.4k citations) and Immunology (818 citations). Robert Redd has collaborated with scholars based in United States, Netherlands and Germany. Frequent co-authors include Donna Neuberg, Scott J. Rodig, Margaret A. Shipp, Philippe Armand, Bjoern Chapuy, Azra H. Ligon, Gordon J. Freeman, Richard T. Hoppe, Courtney Connelly and Daphne de Jong. Their work appears in journals such as Blood, Journal of Clinical Oncology, Blood Advances, British Journal of Haematology and Hematological 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.