W-L Zhao

1.1k total citations
12 papers, 845 citations indexed

About

W-L Zhao is a scholar working on Molecular Biology, Hematology and Pathology and Forensic Medicine. According to data from OpenAlex, W-L Zhao has authored 12 papers receiving a total of 845 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 3 papers in Hematology and 2 papers in Pathology and Forensic Medicine. Recurrent topics in W-L Zhao's work include Acute Myeloid Leukemia Research (3 papers), Retinoids in leukemia and cellular processes (3 papers) and T-cell and Retrovirus Studies (2 papers). W-L Zhao is often cited by papers focused on Acute Myeloid Leukemia Research (3 papers), Retinoids in leukemia and cellular processes (3 papers) and T-cell and Retrovirus Studies (2 papers). W-L Zhao collaborates with scholars based in China, France and Czechia. W-L Zhao's co-authors include Z-X Shen, Shyh‐Jye Chen, Li Dong, Wei Shi, Yan Chen, S J Chen, Dan Xiao, Lin Wang, Anne Janin and JM Li and has published in prestigious journals such as Leukemia, Cell Death and Disease and Bone Marrow Transplantation.

In The Last Decade

W-L Zhao

12 papers receiving 834 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
W-L Zhao China 10 576 263 142 134 124 12 845
Edward Laane Estonia 14 378 0.7× 182 0.7× 68 0.5× 133 1.0× 182 1.5× 27 754
Jinsong Yan China 14 445 0.8× 249 0.9× 218 1.5× 77 0.6× 43 0.3× 66 787
Su-Peng Yeh Taiwan 13 533 0.9× 118 0.4× 213 1.5× 139 1.0× 32 0.3× 29 856
Bin Fu China 14 314 0.5× 249 0.9× 136 1.0× 74 0.6× 31 0.3× 29 647
Laura Cicconi Italy 18 662 1.1× 432 1.6× 99 0.7× 118 0.9× 22 0.2× 32 918
Thomas Moulton United States 15 1.1k 1.9× 116 0.4× 290 2.0× 150 1.1× 34 0.3× 27 1.6k
Jing‐dong Zhou China 20 881 1.5× 506 1.9× 382 2.7× 120 0.9× 53 0.4× 79 1.1k
Yongjun Fang China 17 479 0.8× 116 0.4× 273 1.9× 106 0.8× 60 0.5× 75 852
Saeed Solali Iran 16 603 1.0× 64 0.2× 271 1.9× 129 1.0× 46 0.4× 41 896
Amina Abdul‐Aziz United Kingdom 11 288 0.5× 317 1.2× 128 0.9× 88 0.7× 32 0.3× 18 651

Countries citing papers authored by W-L Zhao

Since Specialization
Citations

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

Fields of papers citing papers by W-L Zhao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by W-L Zhao. 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 W-L Zhao. The network helps show where W-L Zhao may publish in the future.

Co-authorship network of co-authors of W-L Zhao

This figure shows the co-authorship network connecting the top 25 collaborators of W-L Zhao. A scholar is included among the top collaborators of W-L Zhao 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 W-L Zhao. W-L Zhao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
1.
Xiong, Jie, Zhong Zheng, Yiming Zhao, et al.. (2017). MYC is a positive regulator of choline metabolism and impedes mitophagy-dependent necroptosis in diffuse large B-cell lymphoma. Blood Cancer Journal. 7(7). e582–e582. 50 indexed citations
2.
Xiong, Jie, Jun Bian, Ji‐Yuan Zhou, et al.. (2015). Dysregulated choline metabolism in T-cell lymphoma: role of choline kinase-α and therapeutic targeting. Blood Cancer Journal. 5(3). e287–e287. 37 indexed citations
3.
Xue, Kai, Ye Guo, Martha Romero, et al.. (2013). MicroRNA187 overexpression is related to tumor progression and determines sensitivity to bortezomib in peripheral T-cell lymphoma. Leukemia. 28(4). 880–887. 33 indexed citations
4.
Romero, Martha, Philippe Ratajczak, Christophe Lebœuf, et al.. (2012). Increased apoptosis is linked to severe acute GVHD in patients with Fanconi anemia. Bone Marrow Transplantation. 48(6). 849–853. 23 indexed citations
5.
Shi, Wei, Dan Xiao, Lin Wang, et al.. (2012). Therapeutic metformin/AMPK activation blocked lymphoma cell growth via inhibition of mTOR pathway and induction of autophagy. Cell Death and Disease. 3(3). e275–e275. 265 indexed citations
6.
Zhao, W-L. (2009). Targeted therapy in T-cell malignancies: dysregulation of the cellular signaling pathways. Leukemia. 24(1). 13–21. 84 indexed citations
7.
8.
Jiao, Bo, Yang Liang, HM Chen, et al.. (2009). AML1-ETO9a is correlated with C-KIT overexpression/mutations and indicates poor disease outcome in t(8;21) acute myeloid leukemia-M2. Leukemia. 23(9). 1598–1604. 57 indexed citations
9.
Chen, B, W-L Zhao, Jie Jin, et al.. (2005). Clinical and cytogenetic features of 508 Chinese patients with myelodysplastic syndrome and comparison with those in Western countries. Leukemia. 19(5). 767–775. 87 indexed citations
10.
11.
L, Hu, W-L Zhao, & Guo Zeng. (1995). [An epidemiological study on the characteristics of smoking behaviors among 910 young workers in Shangqiu City, Henan Province].. PubMed. 16(1). 3–7. 1 indexed citations
12.
Zhao, W-L, et al.. (1994). [A second discussion on the position of a new species mianbixie].. PubMed. 19(4). 199–200, 255. 3 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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