Sujiang Zhang

1.2k total citations · 1 hit paper
62 papers, 710 citations indexed

About

Sujiang Zhang is a scholar working on Hematology, Genetics and Molecular Biology. According to data from OpenAlex, Sujiang Zhang has authored 62 papers receiving a total of 710 indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Hematology, 27 papers in Genetics and 16 papers in Molecular Biology. Recurrent topics in Sujiang Zhang's work include Acute Myeloid Leukemia Research (32 papers), Chronic Myeloid Leukemia Treatments (23 papers) and Chronic Lymphocytic Leukemia Research (14 papers). Sujiang Zhang is often cited by papers focused on Acute Myeloid Leukemia Research (32 papers), Chronic Myeloid Leukemia Treatments (23 papers) and Chronic Lymphocytic Leukemia Research (14 papers). Sujiang Zhang collaborates with scholars based in China and United States. Sujiang Zhang's co-authors include Jianyong Li, Chun Qiao, Sixuan Qian, Hai‐Rong Qiu, Jingyi Shi, Kourong Miao, Bai-Wei Gu, Xiao‐Dong Gao, Sai‐Juan Chen and Wei Xu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Sujiang Zhang

55 papers receiving 704 citations

Hit Papers

Modified lentiviral globin gene therapy for pediatric β0/... 2024 2026 2025 2024 10 20 30 40

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Sujiang Zhang China 13 368 329 223 149 112 62 710
Lisa Hopcroft United Kingdom 13 489 1.3× 342 1.0× 293 1.3× 141 0.9× 59 0.5× 23 814
Chun Qiao China 15 353 1.0× 318 1.0× 322 1.4× 159 1.1× 136 1.2× 100 825
Guo‐Rui Ruan China 17 453 1.2× 412 1.3× 169 0.8× 178 1.2× 71 0.6× 74 827
Deborah Fuchs United States 8 606 1.6× 368 1.1× 310 1.4× 101 0.7× 50 0.4× 20 882
Matthias Bartenstein United States 8 252 0.7× 387 1.2× 125 0.6× 97 0.7× 196 1.8× 16 661
François G. Kavelaars Netherlands 9 429 1.2× 308 0.9× 204 0.9× 61 0.4× 161 1.4× 24 645
Sarah Moore Australia 12 265 0.7× 175 0.5× 173 0.8× 136 0.9× 48 0.4× 32 563
Brian Parkin United States 16 374 1.0× 317 1.0× 198 0.9× 212 1.4× 134 1.2× 44 790
I. Quiquandon France 12 459 1.2× 226 0.7× 210 0.9× 276 1.9× 89 0.8× 17 774
Lucia Casarino Italy 13 323 0.9× 162 0.5× 163 0.7× 131 0.9× 50 0.4× 26 608

Countries citing papers authored by Sujiang Zhang

Since Specialization
Citations

This map shows the geographic impact of Sujiang 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 Sujiang Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sujiang Zhang more than expected).

Fields of papers citing papers by Sujiang Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sujiang 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 Sujiang Zhang. The network helps show where Sujiang Zhang may publish in the future.

Co-authorship network of co-authors of Sujiang Zhang

This figure shows the co-authorship network connecting the top 25 collaborators of Sujiang Zhang. A scholar is included among the top collaborators of Sujiang Zhang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sujiang Zhang. Sujiang Zhang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
2.
Zhang, Zilu, Jingtao Huang, Luxiang Wang, et al.. (2024). COVID-19 in immunocompromised patients after hematopoietic stem cell transplantation: a pilot study. SHILAP Revista de lepidopterología. 6(2). e00183–e00183. 1 indexed citations
3.
Zhu, Yongmei, Jianfeng Li, Guang Yang, et al.. (2023). Picalm::MLLT10 can Identify a New Subgroup of Acute Leukemias of Ambiguous Lineage with Unique Extramedullary Disease and Treatment Response. Blood. 142(Supplement 1). 6078–6078.
4.
Niu, Q. L., Yang Shen, Hai Fang, et al.. (2021). Integration of Genomic and Transcriptomic Markers Improves the Prognosis Prediction of Acute Promyelocytic Leukemia. Clinical Cancer Research. 27(13). 3683–3694. 15 indexed citations
5.
Yu, Wenyan, Mei Geng, Jie Hao, et al.. (2017). Clinical Features and Prognosis Analysis of Hodgkin Lymphoma: A Multicenter Retrospective Study Over a Decade of Patients in China. Clinical Lymphoma Myeloma & Leukemia. 17(5). 274–282. 4 indexed citations
6.
Chen, Weifeng, et al.. (2015). [The clinical significance of serum neopterin and adenosine deaminase in patients with secondary hemophagocytic lymphohistiocytosis].. PubMed. 54(1). 44–7. 2 indexed citations
8.
Zhang, Lijuan, et al.. (2012). The significance of 18F-FDG PET/CT in secondary hemophagocytic lymphohistiocytosis. Journal of Hematology & Oncology. 5(1). 40–40. 14 indexed citations
9.
Zhang, Li-Juan, Sujiang Zhang, Ji Xu, et al.. (2011). Splenectomy for an adult patient with refractory secondary hemophagocytic lymphohistiocytosis. Biomedicine & Pharmacotherapy. 65(6). 432–435. 7 indexed citations
10.
Zhu, Yuandong, Li Wang, Chao Sun, et al.. (2011). Distinctive microRNA signature is associated with the diagnosis and prognosis of acute leukemia. Medical Oncology. 29(4). 2323–2331. 45 indexed citations
11.
Zhu, Yu, et al.. (2011). Detection of BCR-ABL fusion proteins in patients with leukemia using a cytometric bead array. Leukemia & lymphoma. 53(3). 451–455. 7 indexed citations
12.
Zhang, Sujiang, Jingyi Shi, & Jianyong Li. (2009). GATA-2 L359 V mutation is exclusively associated with CML progression but not other hematological malignancies and GATA-2 P250A is a novel single nucleotide polymorphism. Leukemia Research. 33(8). 1141–1143. 25 indexed citations
13.
Zhang, Sujiang, Liyuan Ma, Qiuhua Huang, et al.. (2008). Gain-of-function mutation of GATA-2 in acute myeloid transformation of chronic myeloid leukemia. Proceedings of the National Academy of Sciences. 105(6). 2076–2081. 129 indexed citations
14.
Xu, Wei, Jianyong Li, Jun Xia, et al.. (2008). MPL W515L mutation in Chinese patients with myeloproliferative diseases. Leukemia & lymphoma. 49(5). 955–958. 9 indexed citations
15.
Zhang, Sujiang, et al.. (2008). JAK2V617F patients with essential thrombocythemia present with clinical features of polycythemia vera. Leukemia & lymphoma. 49(4). 696–699. 10 indexed citations
16.
Li, Jianyong, Wei Xu, Wei Wu, et al.. (2008). The Negative Prognostic Impact of Derivative 9 Deletions in Patients Who Received Hydroxyurea Treatment for Chronic Myelogenous Leukemia in the Chronic Phase. Oncology Research and Treatment. 31(11). 585–589. 3 indexed citations
17.
Zhang, Sujiang. (2008). The role of aberrant transcription factor in the progression of chronic myeloid leukemia. Leukemia & lymphoma. 49(8). 1463–1469. 4 indexed citations
18.
Xu, Wei, Jianyong Li, Sixuan Qian, et al.. (2007). Outcome of treatment with Hyper-CVAD regimen in Chinese patients with acute lymphocytic leukemia. Leukemia Research. 32(6). 930–935. 12 indexed citations
19.
Zhang, Sujiang, Jianyong Li, Jingyi Shi, et al.. (2006). [Study of mutation and single nucleotide polymorphism of PDGFRbeta and SHIP gene in acute myeloid leukemia].. PubMed. 27(6). 383–5. 1 indexed citations
20.
Shi, Jingyi, Zhanzhong Shi, Sujiang Zhang, et al.. (2004). Association between single nucleotide polymorphisms in deoxycytidine kinase and treatment response among acute myeloid leukaemia patients. Pharmacogenetics. 14(11). 759–768. 57 indexed citations

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.

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