Shengjun Ji

776 citations
57 papers · 536 · h-index 12

Impact in

Papers in

    • Inflammatory Biomarkers in Disease Prognosis 11
    • Cancer Immunotherapy and Biomarkers 3
    • Cancer-related cognitive impairment studies 7
    • Ferroptosis and cancer prognosis 4

Shengjun Ji

52 papers receiving 529 citations

Peers

Shengjun Ji
Comparison fields: 5 of 74
  • Developmental Neuroscience 73
  • Oncology 131
  • Neurology 39
  • Dermatology 34
  • Genetics 38
Replace Melissa A. Yates with:
Melissa A. Yates United States
Kenji Akazawa Japan
Weibin Lin China
M. Rieks Germany
J Colon United States
Giorgia Leone Italy
Naoki Nitta Japan
Ming Huang China
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Citations per field
00.5×9.5×
Melissa A. Yates · 1×
Citations per year

Countries citing papers authored by Shengjun Ji

Since Specialization
Citations

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

Fields of papers citing papers by Shengjun Ji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Shengjun Ji, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Shengjun Ji Line = papers co-authored together Shengjun Ji links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201398
2 201956
3 201446
4 201439
5 202332
6 201218
7 201918
8 202015
9 202213
10 202212
11 201712
12 202111
13 202511
14 202111
15 202311
16 20219
17 20239
18 20238
19 20188
20 20247

About Shengjun Ji

Shengjun Ji is a scholar working on Oncology, Pulmonary and Respiratory Medicine, Molecular Biology, Cancer Research and Obstetrics and Gynecology, having authored 57 papers that have together received 536 indexed citations. Recurring topics across this work include Inflammatory Biomarkers in Disease Prognosis (11 papers), Cancer-related cognitive impairment studies (7 papers), Neurogenesis and neuroplasticity mechanisms (6 papers), Endometrial and Cervical Cancer Treatments (6 papers), Ferroptosis and cancer prognosis (4 papers), Cancer, Lipids, and Metabolism (4 papers), Cancer Immunotherapy and Biomarkers (3 papers) and Esophageal Cancer Research and Treatment (3 papers). The work is most often cited by research in Developmental Neuroscience (73 citations), Oncology (131 citations), Neurology (39 citations), Dermatology (34 citations) and Genetics (38 citations). Shengjun Ji has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Liyuan Zhang, Ye Tian, Jianfeng Ji, Rui Sun, Yuan Zhang, Kun Li, Xinwei Guo, Jinchang Wu, Ke Gu and Xiaochen Chen. Their work appears in journals such as Cancer Management and Research, Journal of Inflammation Research, International Journal of Radiation Oncology*Biology*Physics, Journal of Cancer and Frontiers in Immunology.

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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