Ling-Di Li

531 total citations
45 papers, 398 citations indexed

About

Ling-Di Li is a scholar working on Hematology, Molecular Biology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Ling-Di Li has authored 45 papers receiving a total of 398 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Hematology, 25 papers in Molecular Biology and 8 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Ling-Di Li's work include Acute Myeloid Leukemia Research (19 papers), Multiple Myeloma Research and Treatments (8 papers) and Acute Lymphoblastic Leukemia research (8 papers). Ling-Di Li is often cited by papers focused on Acute Myeloid Leukemia Research (19 papers), Multiple Myeloma Research and Treatments (8 papers) and Acute Lymphoblastic Leukemia research (8 papers). Ling-Di Li collaborates with scholars based in China, United Kingdom and United States. Ling-Di Li's co-authors include Xiao‐Jun Huang, Ya‐Zhen Qin, Jinlan Li, Pin Wu, Bin Jiang, Dang Wu, Qun Yu, Lijun Li, Guo‐Rui Ruan and Yanrong Liu and has published in prestigious journals such as Scientific Reports, Biochemical and Biophysical Research Communications and International Journal of Hydrogen Energy.

In The Last Decade

Ling-Di Li

43 papers receiving 393 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ling-Di Li China 11 210 196 84 65 60 45 398
Anthony M. Hunter United States 10 119 0.6× 254 1.3× 134 1.6× 48 0.7× 28 0.5× 41 326
E. Regazzi Italy 10 121 0.6× 231 1.2× 185 2.2× 112 1.7× 33 0.6× 17 428
Chengming Fei China 13 234 1.1× 230 1.2× 142 1.7× 90 1.4× 14 0.2× 25 495
Vitina Grieco Italy 12 216 1.0× 135 0.7× 93 1.1× 101 1.6× 15 0.3× 21 389
Emiliano Fabiani Italy 18 419 2.0× 444 2.3× 184 2.2× 101 1.6× 96 1.6× 48 695
D. Garau Italy 13 115 0.5× 340 1.7× 192 2.3× 110 1.7× 67 1.1× 29 502
Yaozhong Zhao China 10 184 0.9× 92 0.5× 65 0.8× 149 2.3× 25 0.4× 47 410
Shirin Azizidoost Iran 12 256 1.2× 120 0.6× 83 1.0× 80 1.2× 23 0.4× 44 465
Friederike Braulke Germany 10 66 0.3× 190 1.0× 102 1.2× 57 0.9× 20 0.3× 31 305

Countries citing papers authored by Ling-Di Li

Since Specialization
Citations

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

Fields of papers citing papers by Ling-Di Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ling-Di Li. 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-Di Li. The network helps show where Ling-Di Li may publish in the future.

Co-authorship network of co-authors of Ling-Di Li

This figure shows the co-authorship network connecting the top 25 collaborators of Ling-Di Li. A scholar is included among the top collaborators of Ling-Di Li 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 Ling-Di Li. Ling-Di Li 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
1.
Li, Ling-Di, et al.. (2025). Spatiotemporal evolution patterns of the coupling of carbon productivity and high-quality economic development in China. Scientific Reports. 15(1). 9114–9114. 3 indexed citations
2.
Tang, Rongjun, Qing Yao, Ke Zhang, et al.. (2025). Revolutionizing prognosis: Introducing cell death index (CDI) as a powerful prognostic tool for CSCC patients. Environmental Toxicology. 40(3). 481–492. 1 indexed citations
3.
Tang, Rongjun, Lidan Zhang, Jun Lou, et al.. (2025). Formononetin prevents intestinal injury caused by radiotherapy in colorectal cancer mice via the Keap1-Nrf2 signaling pathway. Biochemical and Biophysical Research Communications. 761. 151676–151676. 2 indexed citations
4.
Yu, Qingqing, et al.. (2024). Baicalein Enhances Radiosensitivity in Colorectal Cancer via JAK2/STAT3 Pathway Inhibition. Chemical Biology & Drug Design. 104(2). e14611–e14611. 3 indexed citations
5.
6.
Chen, Wen‐Ming, Ling-Di Li, Xu Wang, et al.. (2023). High WT1 expression predicted induction chemotherapy failure in acute myeloid leukemia patients with non-favorable cytogenetic risk. Clinical and Experimental Medicine. 23(6). 2629–2638. 4 indexed citations
7.
Wang, Yazhe, Wen‐Ming Chen, Jun Wang, et al.. (2022). Low IL7R Expression at Diagnosis Predicted Relapse in Adult Acute Myeloid Leukemia Patients With t(8;21). Frontiers in Immunology. 13. 909104–909104. 1 indexed citations
8.
Li, Ling-Di, et al.. (2021). Molecular characterization of metabolic subtypes of gastric cancer based on metabolism-related lncRNA. Scientific Reports. 11(1). 21491–21491. 7 indexed citations
9.
Lu, Aidong, Wen‐Ming Chen, Ling-Di Li, et al.. (2021). Low EVI1 expression at diagnosis predicted poor outcomes in pediatric Ph-negative B cell precursor acute lymphoblastic leukemia patients. Pediatric Hematology and Oncology. 39(2). 97–107. 1 indexed citations
10.
Wang, Hongqiang, et al.. (2021). Effect of targeted nursing intervention plus psychological counseling on quality of life, negative emotions, and complications in patients with extensively drug-resistant tuberculosis.. PubMed. 13(12). 13950–13958. 4 indexed citations
11.
Chang, Yan, Yazhe Wang, Ling-Di Li, et al.. (2020). <p>Both Methylation and Copy Number Variation Participated in the Varied Expression of PRAME in Multiple Myeloma</p>. OncoTargets and Therapy. Volume 13. 7545–7553. 3 indexed citations
12.
Wang, Yazhe, Hong‐Hu Zhu, Yan Chang, et al.. (2017). PRAME Gene Copy Number Variation Is Related to Its Expression in Multiple Myeloma. DNA and Cell Biology. 36(12). 1099–1107. 19 indexed citations
13.
Lu, Aidong, et al.. (2016). PRAME overexpression predicted good outcome in pediatric B-cell acute lymphoblastic leukemia patients receiving chemotherapy. Leukemia Research. 52. 43–49. 15 indexed citations
14.
Li, Ning, Robert Peter Gale, Jinlan Li, et al.. (2015). Frequency and allele burden of CALR mutations in Chinese with essential thrombocythemia and primary myelofibrosis without JAK2V617F or MPL mutations. Leukemia Research. 39(5). 510–514. 15 indexed citations
15.
Zhang, Yao, Bao Li, Jin Lu, et al.. (2014). The clinical value of the quantitative detection of four cancer-testis antigen genes in multiple myeloma. Molecular Cancer. 13(1). 25–25. 8 indexed citations
16.
Liu, Yanrong, Hong‐Hu Zhu, Guo‐Rui Ruan, et al.. (2013). NPM1-mutated acute myeloid leukemia of monocytic or myeloid origin exhibit distinct immunophenotypes. Leukemia Research. 37(7). 737–741. 28 indexed citations
17.
18.
Qin, Ya‐Zhen, Hong‐Hu Zhu, Yanrong Liu, et al.. (2012). PRAME and WT1 transcripts constitute a good molecular marker combination for monitoring minimal residual disease in myelodysplastic syndromes. Leukemia & lymphoma. 54(7). 1442–1449. 22 indexed citations
19.
Li, Henan, Yao Zhang, Jinlan Li, et al.. (2010). Aberrant expression of CKLF-like MARVEL transmembrane member 5 (CMTM5) by promoter methylation in myeloid leukemia. Leukemia Research. 35(6). 771–776. 22 indexed citations
20.
Qin, Ya‐Zhen, Jinlan Li, Hong‐Hu Zhu, et al.. (2007). [Detection of common fusion transcript levels in untreated leukemia patients by real-time quantitative RT-PCR technique].. PubMed. 28(7). 433–7. 7 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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