Kyle A. Udd
Impact in
- Hematology top 5%
- Multiple Myeloma Research and Treatments
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- CAR-T cell therapy research
- Peptidase Inhibition and Analysis
Papers in
- Hematology 15
- Multiple Myeloma Research and Treatments 15
- Oncology 13
- Peptidase Inhibition and Analysis 9
- Cancer Treatment and Pharmacology 3
- Co-authors
- James R. Berenson (25 shared papers)Tanya M. Spektor (16 shared papers)Regina A. Swift (14 shared papers)Mingjie Li (15 shared papers)Eric Sanchez (16 shared papers)Haiming Chen (14 shared papers)Suzie Vardanyan (7 shared papers)Cathy S. Wang (9 shared papers)
- Journals
- Blood (11 papers)Targeted Oncology (2 papers)European Journal Of Haematology (2 papers)Supportive Care in Cancer (2 papers)Annals of Hematology (2 papers)
- Partner nations
- United States
In The Last Decade
Kyle A. Udd
25 papers receiving 303 citations
Peers
Comparison fields: 5 of 40
- Hematology 197
- Oncology 202
- Radiology, Nuclear Medicine and Imaging 99
- Genetics 32
- Immunology 51
Countries citing papers authored by Kyle A. Udd
This map shows the geographic impact of Kyle A. Udd'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 Kyle A. Udd with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kyle A. Udd more than expected).
Fields of papers citing papers by Kyle A. Udd
This network shows the impact of papers produced by Kyle A. Udd. 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 Kyle A. Udd. The network helps show where Kyle A. Udd may publish in the future.
Co-authors
The 25 scholars most cited alongside Kyle A. Udd, 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 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 140 | |
| 2 | 2016 | 28 | |
| 3 | 2017 | 18 | |
| 4 | 2021 | 15 | |
| 5 | 2019 | 15 | |
| 6 | 2016 | 14 | |
| 7 | 2016 | 12 | |
| 8 | Monitoring multiple myeloma. | 2017 | 9 |
| 9 | 2017 | 6 | |
| 10 | 2016 | 6 | |
| 11 | 2016 | 6 | |
| 12 | 2015 | 6 | |
| 13 | 2017 | 5 | |
| 14 | 2014 | 5 | |
| 15 | 2019 | 5 | |
| 16 | 2018 | 3 | |
| 17 | 2017 | 2 | |
| 18 | 2017 | 2 | |
| 19 | 2017 | 2 | |
| 20 | 2016 | 2 |
About Kyle A. Udd
Kyle A. Udd is a scholar working on Hematology, Oncology, Radiology, Nuclear Medicine and Imaging, Molecular Biology and Genetics, having authored 25 papers that have together received 307 indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (15 papers), Monoclonal and Polyclonal Antibodies Research (10 papers), Peptidase Inhibition and Analysis (9 papers), Chronic Lymphocytic Leukemia Research (6 papers), Lymphoma Diagnosis and Treatment (4 papers), Protein Degradation and Inhibitors (3 papers), Cancer Treatment and Pharmacology (3 papers) and HIV/AIDS drug development and treatment (3 papers). The work is most often cited by research in Hematology (197 citations), Oncology (202 citations), Radiology, Nuclear Medicine and Imaging (99 citations), Genetics (32 citations) and Immunology (51 citations). Kyle A. Udd has collaborated with scholars based in United States. Frequent co-authors include James R. Berenson, Tanya M. Spektor, Regina A. Swift, Mingjie Li, Eric Sanchez, Haiming Chen, Suzie Vardanyan, Cathy S. Wang, Nika M Harutyunyan and Claudia Andreu‐Vieyra. Their work appears in journals such as Blood, Targeted Oncology, European Journal Of Haematology, Supportive Care in Cancer and Annals of Hematology.
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.