Keqin Qi
Impact in
- Hematology top 5%
- Multiple Myeloma Research and Treatments
-
- CAR-T cell therapy research
- Peptidase Inhibition and Analysis
Papers in
- Hematology 23
- Multiple Myeloma Research and Treatments 23
- Oncology 15
- Peptidase Inhibition and Analysis 6
- CAR-T cell therapy research 3
- Cancer Treatment and Pharmacology 2
- Co-authors
- Brian Forsyth (1 shared paper)John M. Leventhal (1 shared paper)Saad Z. Usmani (12 shared papers)Katherine Chastain (9 shared papers)Arnob Banerjee (5 shared papers)Thomas S. Lin (4 shared papers)Sriya Gunawardena (3 shared papers)Ming Qi (4 shared papers)
- Journals
- Journal of Clinical Oncology (9 papers)Blood (4 papers)HemaSphere (2 papers)Cancer (1 paper)British Journal of Haematology (1 paper)
- Partner nations
- United StatesSpainBelgium
In The Last Decade
Keqin Qi
29 papers receiving 345 citations
Peers
Comparison fields: 5 of 49
- Hematology 164
- Oncology 180
- Genetics 47
- Pathology and Forensic Medicine 64
- Pediatrics, Perinatology and Child Health 41
Countries citing papers authored by Keqin Qi
This map shows the geographic impact of Keqin Qi'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 Keqin Qi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keqin Qi more than expected).
Fields of papers citing papers by Keqin Qi
This network shows the impact of papers produced by Keqin Qi. 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 Keqin Qi. The network helps show where Keqin Qi may publish in the future.
Co-authors
The 25 scholars most cited alongside Keqin Qi, 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 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1997 | 61 | |
| 2 | 2019 | 49 | |
| 3 | 2023 | 36 | |
| 4 | 2022 | 35 | |
| 5 | 2023 | 22 | |
| 6 | 2021 | 20 | |
| 7 | 2021 | 19 | |
| 8 | 2019 | 16 | |
| 9 | 2023 | 10 | |
| 10 | 2022 | 10 | |
| 11 | 2019 | 9 | |
| 12 | 2018 | 9 | |
| 13 | 2023 | 8 | |
| 14 | 2024 | 7 | |
| 15 | 2023 | 7 | |
| 16 | 2021 | 5 | |
| 17 | 2021 | 4 | |
| 18 | 2024 | 3 | |
| 19 | 2020 | 3 | |
| 20 | 2024 | 3 |
About Keqin Qi
Keqin Qi is a scholar working on Hematology, Oncology, Molecular Biology, Genetics and Pathology and Forensic Medicine, having authored 33 papers that have together received 348 indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (23 papers), Protein Degradation and Inhibitors (9 papers), Chronic Lymphocytic Leukemia Research (7 papers), Peptidase Inhibition and Analysis (6 papers), Lymphoma Diagnosis and Treatment (4 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), CAR-T cell therapy research (3 papers) and Cancer Treatment and Pharmacology (2 papers). The work is most often cited by research in Hematology (164 citations), Oncology (180 citations), Genetics (47 citations), Pathology and Forensic Medicine (64 citations) and Pediatrics, Perinatology and Child Health (41 citations). Keqin Qi has collaborated with scholars based in United States, Spain and Belgium. Frequent co-authors include Brian Forsyth, John M. Leventhal, Saad Z. Usmani, Katherine Chastain, Arnob Banerjee, Thomas S. Lin, Sriya Gunawardena, Ming Qi, Mohit Narang and Yana Lutska. Their work appears in journals such as Journal of Clinical Oncology, Blood, HemaSphere, Cancer and British Journal of Haematology.
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.