Kaijun Di

825 citations
26 papers · 621 · h-index 13

Impact in

Papers in

    • Ubiquitin and proteasome pathways 8
    • Mitochondrial Function and Pathology 4
    • Glioma Diagnosis and Treatment 13

Kaijun Di

23 papers receiving 618 citations

Peers

Kaijun Di
Comparison fields: 5 of 75
  • Genetics 133
  • Pulmonary and Respiratory Medicine 190
  • Developmental Neuroscience 21
  • Cancer Research 75
  • Molecular Biology 308
Replace Ganeshkumar Rajendran with:
Ganeshkumar Rajendran United States
Ruolan Han United States
Kathryn Graham Canada
Min Chao China
Robert J. Corona United States
Pengzhan Zhao China
Junwen Hu China
Alireza Azimi Sweden
Michał Rynkowski Poland
Nanxiang Xiong China
Kaijun Di relative to Ganeshkumar Rajendran United States Ganeshkumar Rajendran's profile →
Citations per field
00.5×1.5×2.3×
Ganeshkumar Rajendran · 1×
Citations per year

Countries citing papers authored by Kaijun Di

Since Specialization
Citations

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

Fields of papers citing papers by Kaijun Di

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Kaijun Di, 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 Kaijun Di Line = papers co-authored together Kaijun Di links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016128
2 2015109
3 201490
4 201260
5 201732
6 200730
7 201630
8 200628
9 202023
10 201420
11 200820
12 201516
13 201812
14 202411
15 20192
16 20232
17 20212
18 20161
19 20201
20 20141

About Kaijun Di

Kaijun Di is a scholar working on Molecular Biology, Genetics, Pulmonary and Respiratory Medicine, Oncology and Cancer Research, having authored 26 papers that have together received 621 indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (13 papers), Ubiquitin and proteasome pathways (8 papers), Cancer-related cognitive impairment studies (6 papers), Mitochondrial Function and Pathology (4 papers), Brain Metastases and Treatment (3 papers), Cancer, Hypoxia, and Metabolism (3 papers), Ferroptosis and cancer prognosis (2 papers) and Cancer Genomics and Diagnostics (2 papers). The work is most often cited by research in Genetics (133 citations), Pulmonary and Respiratory Medicine (190 citations), Developmental Neuroscience (21 citations), Cancer Research (75 citations) and Molecular Biology (308 citations). Kaijun Di has collaborated with scholars based in United States, Hong Kong and Romania. Frequent co-authors include Daniela A. Bota, Naomi Lomeli, John F. Guzowski, Xing Gong, J Czerniawski, Mark E. Linskey, Yong Chuan Wong, Ann MacLaren, Francis Burrows and Annick Desjardins. Their work appears in journals such as Neuro-Oncology, Cancer Research, Journal of Neuro-Oncology, Experimental Neurology and Oncogene.

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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