Ling Zhang
- Infectious Diseases top 2%
- Hematology top 2%
- Acute Myeloid Leukemia Research 51
- Chronic Myeloid Leukemia Treatments 23
- Multiple Myeloma Research and Treatments 9
- Genetics top 5%
- Myeloproliferative Neoplasms: Diagnosis and Treatment 18
- Chronic Lymphocytic Leukemia Research 15
- Modeling and Simulation top 5%
- Neurology top 10%
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- Lymphoma Diagnosis and Treatment 15
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- Acute Lymphoblastic Leukemia research 13
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- Cutaneous lymphoproliferative disorders research 10
- Journals
- Blood (38 papers)Archives of Pathology & Laboratory Medicine (4 papers)Frontiers in Oncology (4 papers)
- Partner nations
- United StatesChinaNetherlands
In The Last Decade
Ling Zhang
99 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 116
- Infectious Diseases 673
- Hematology 383
- Genetics 223
- Modeling and Simulation 80
- Neurology 188
Countries citing papers authored by Ling Zhang
This map shows the geographic impact of Ling Zhang'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 Ling Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ling Zhang more than expected).
Fields of papers citing papers by Ling Zhang
This network shows the impact of papers produced by Ling Zhang. 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 Ling Zhang. The network helps show where Ling Zhang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ling Zhang, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 0 | |
| 5 | 2023 | 7 | |
| 6 | 2023 | 0 | |
| 7 | 2023 | 13 | |
| 8 | 2022 | 1 | |
| 9 | 2021 | 1 | |
| 10 | 2020 | 5 | |
| 11 | 2019 | 5 | |
| 12 | 2019 | 1 | |
| 13 | 2018 | 0 | |
| 14 | 2017 | 4 | |
| 15 | 2014 | 3 | |
| 16 | 2014 | 26 | |
| 17 | 2014 | 24 | |
| 18 | [Correlation of CD19 positive cell counts in bone marrow with therapeutic efficacy in patients with multiple myeloma]. | 2011 | 1 |
| 19 | 2010 | 41 | |
| 20 | [Quality evaluation of prepared slices of Paeonia lactiflon--determination of paeoniflorin by HPLC]. | 2004 | 4 |
About Ling Zhang
Ling Zhang is a scholar working on Hematology, Genetics and Dermatology, having authored 113 papers that have together received 1.8k indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (51 papers), Chronic Myeloid Leukemia Treatments (23 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (18 papers), Chronic Lymphocytic Leukemia Research (15 papers), Lymphoma Diagnosis and Treatment (15 papers), Acute Lymphoblastic Leukemia research (13 papers), Cutaneous lymphoproliferative disorders research (10 papers) and Multiple Myeloma Research and Treatments (9 papers). The work is most often cited by research in Infectious Diseases (673 citations), Hematology (383 citations) and Genetics (223 citations). Ling Zhang has collaborated with scholars based in United States, China and Netherlands. Frequent co-authors include Hua Zhu, Zhiqi Song, Yajin Qu, Pin Yü, Chuan Qin, Wenjie Zhao, Linlin Bao, Yanfeng Xu, Yunlin Han and Lubomir Sokol. Their work appears in journals such as Blood, Archives of Pathology & Laboratory Medicine, Frontiers in Oncology, Leukemia Research and Journal of Clinical 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.