Ming Qi
Impact in
- Hematology top 0.5%
- Multiple Myeloma Research and Treatments
- Oncology top 2%
- Peptidase Inhibition and Analysis
Papers in
- Hematology 69
- Multiple Myeloma Research and Treatments 68
- Genetics 29
- Chronic Lymphocytic Leukemia Research 27
- Co-authors
- Xiang QinWojciech ZarębaScott McNittJennifer L. RobinsonArthur J. MossIlan GoldenbergMaría‐Victoria MateosTahamtan Ahmadi
- Journals
- Blood (30 papers)Journal of Clinical Oncology (18 papers)British Journal of Haematology (4 papers)Clinical Cancer Research (3 papers)Annals of Hematology (3 papers)
- Partner nations
- United StatesSpainBelgium
In The Last Decade
Ming Qi
105 papers receiving 3.7k citations
Hit Papers
Peers
Comparison fields: 5 of 114
- Hematology 1.8k
- Oncology 1.5k
- Cardiology and Cardiovascular Medicine 1.1k
- Genetics 369
- Molecular Biology 1.8k
Countries citing papers authored by Ming Qi
This map shows the geographic impact of Ming 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 Ming Qi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Qi more than expected).
Fields of papers citing papers by Ming Qi
This network shows the impact of papers produced by Ming 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 Ming Qi. The network helps show where Ming Qi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ming 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
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 3 | |
| 2 | 2021 | 5 | |
| 3 | 2020 | 11 | |
| 4 | 2020 | 9 | |
| 5 | 2020 | 6 | |
| 6 | 2019 | 26 | |
| 7 | 2019 | 7 | |
| 8 | 2018 | 103 | |
| 9 | 2017 | 8 | |
| 10 | 2017 | 5 | |
| 11 | 2017 | 5 | |
| 12 | 2017 | 3 | |
| 13 | 2014 | 6 | |
| 14 | 2013 | 166 | |
| 15 | 2013 | 13 | |
| 16 | 2012 | 54 | |
| 17 | 2012 | 20 | |
| 18 | 2010 | 84 | |
| 19 | 2007 | 214 | |
| 20 | 2005 | 90 |
About Ming Qi
Ming Qi is a scholar working on Hematology, Genetics, Oncology, Pathology and Forensic Medicine and Radiology, Nuclear Medicine and Imaging, having authored 106 papers that have together received 3.8k indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (68 papers), Chronic Lymphocytic Leukemia Research (27 papers), Peptidase Inhibition and Analysis (20 papers), Lymphoma Diagnosis and Treatment (17 papers), Monoclonal and Polyclonal Antibodies Research (16 papers), Protein Degradation and Inhibitors (15 papers), Viral-associated cancers and disorders (14 papers) and Cardiac electrophysiology and arrhythmias (14 papers). The work is most often cited by research in Hematology (1.8k citations), Oncology (1.5k citations), Cardiology and Cardiovascular Medicine (1.1k citations), Genetics (369 citations) and Molecular Biology (1.8k citations). Ming Qi has collaborated with scholars based in United States, Spain and Belgium. Frequent co-authors include Xiang Qin, Wojciech Zaręba, Scott McNitt, Jennifer L. Robinson, Arthur J. Moss, Ilan Goldenberg, María‐Victoria Mateos, Tahamtan Ahmadi, Katja Weisel and Ajay K. Nooka. Their work appears in journals such as Blood, Journal of Clinical Oncology, British Journal of Haematology, Clinical Cancer Research 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.