Lingkai Kong

426 citations
22 papers · 259 · h-index 9

Impact in

    • CAR-T cell therapy research
    • Cancer Immunotherapy and Biomarkers
    • Virus-based gene therapy research

Papers in

Lingkai Kong

18 papers receiving 256 citations

Peers

Lingkai Kong
Comparison fields: 5 of 50
  • Oncology 108
  • Genetics 101
  • Biotechnology 28
  • Geriatrics and Gerontology 8
  • Cancer Research 26
Replace Carmelina Antonella Iannuzzi with:
Carmelina Antonella Iannuzzi Italy
Kohsuke Kato Japan
Alessandro Bonetti United Kingdom
XY Liu China
Christopher B. Driscoll United States
M M Georgescu United States
Kimiko Yoshida Japan
Gary Keeney United States
Danyuan Li China
Lingkai Kong relative to Carmelina Antonella Iannuzzi Italy Carmelina Antonella Iannuzzi's profile →
Citations per field
00.5×10.5×
Carmelina Antonella Iannuzzi · 1×
Citations per year

Countries citing papers authored by Lingkai Kong

Since Specialization
Citations

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

Fields of papers citing papers by Lingkai Kong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202161
2 201935
3 202131
4 202327
5 201826
6 202516
7 202412
8 202412
9 202211
10 20236
11 20245
12 20244
13 20244
14 20193
15 20232
16 20252
17 20251
18 20231
19 20260
20 20250

About Lingkai Kong

Lingkai Kong is a scholar working on Genetics, Molecular Biology, Pulmonary and Respiratory Medicine, Oncology and Cancer Research, having authored 22 papers that have together received 259 indexed citations. Recurring topics across this work include Virus-based gene therapy research (8 papers), Ferroptosis and cancer prognosis (3 papers), Industrial Vision Systems and Defect Detection (2 papers), Cancer, Lipids, and Metabolism (2 papers), Cancer Research and Treatments (2 papers), RNA modifications and cancer (2 papers), CAR-T cell therapy research (2 papers) and Advanced Neural Network Applications (1 paper). The work is most often cited by research in Oncology (108 citations), Genetics (101 citations), Biotechnology (28 citations), Geriatrics and Gerontology (8 citations) and Cancer Research (26 citations). Lingkai Kong has collaborated with scholars based in China, Germany and Ireland. Frequent co-authors include Junhua Wu, Shuguang Zuo, Jie Dong, Jiwu Wei, Min Wei, Shibing Wang, Tiancheng Xu, Shiqun Wang, Chunping Jiang and Xiaosong Gu. Their work appears in journals such as Cell Reports Medicine, Journal of Experimental & Clinical Cancer Research, BMC Cancer, Applied Sciences and JCI Insight.

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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