Jay Yang
Impact in
- Hematology top 5%
- Acute Myeloid Leukemia Research
Papers in
- Hematology 27
- Acute Myeloid Leukemia Research 19
- Chronic Myeloid Leukemia Treatments 7
- Genetics 9
- Myeloproliferative Neoplasms: Diagnosis and Treatment 6
- Co-authors
- Grant W. Brown (7 shared papers)JW Taub (5 shared papers)Holly J. Edwards (5 shared papers)Yongwei Su (5 shared papers)Yubin Ge (5 shared papers)Maik Hüttemann (3 shared papers)Jenna L. Carter (3 shared papers)Katie Hege-Hurrish (2 shared papers)
- Journals
- Blood (13 papers)Hematological Oncology (3 papers)Journal of Pain (3 papers)International Journal of Radiation Oncology*Biology*Physics (2 papers)Haematologica (2 papers)
- Partner nations
- United StatesCanadaChina
In The Last Decade
Jay Yang
64 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 80
- Hematology 227
- Oncology 189
- Molecular Biology 516
- Cancer Research 75
- Genetics 54
Countries citing papers authored by Jay Yang
This map shows the geographic impact of Jay Yang'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 Jay Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay Yang more than expected).
Fields of papers citing papers by Jay Yang
This network shows the impact of papers produced by Jay Yang. 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 Jay Yang. The network helps show where Jay Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Jay Yang, 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 67 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 156 | |
| 2 | 2022 | 102 | |
| 3 | 2002 | 101 | |
| 4 | 2005 | 76 | |
| 5 | 2010 | 59 | |
| 6 | 2019 | 55 | |
| 7 | 2014 | 38 | |
| 8 | 2020 | 37 | |
| 9 | 2012 | 32 | |
| 10 | 2018 | 32 | |
| 11 | 2022 | 27 | |
| 12 | 2012 | 27 | |
| 13 | 2016 | 23 | |
| 14 | 2022 | 21 | |
| 15 | 2021 | 19 | |
| 16 | 2015 | 19 | |
| 17 | 2020 | 15 | |
| 18 | 2022 | 13 | |
| 19 | 2023 | 13 | |
| 20 | 2019 | 11 |
About Jay Yang
Jay Yang is a scholar working on Hematology, Genetics, Molecular Biology, Pathology and Forensic Medicine and Oncology, having authored 67 papers that have together received 1.0k indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (19 papers), Protein Degradation and Inhibitors (7 papers), Chronic Myeloid Leukemia Treatments (7 papers), Lymphoma Diagnosis and Treatment (7 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (6 papers), Histone Deacetylase Inhibitors Research (6 papers), DNA Repair Mechanisms (6 papers) and Neonatal Respiratory Health Research (4 papers). The work is most often cited by research in Hematology (227 citations), Oncology (189 citations), Molecular Biology (516 citations), Cancer Research (75 citations) and Genetics (54 citations). Jay Yang has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Grant W. Brown, JW Taub, Holly J. Edwards, Yongwei Su, Yubin Ge, Maik Hüttemann, Jenna L. Carter, Katie Hege-Hurrish, Hasini A. Kalpage and Chaoying Zhang. Their work appears in journals such as Blood, Hematological Oncology, Journal of Pain, International Journal of Radiation Oncology*Biology*Physics and Haematologica.
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.