Zejun Li

1.2k citations
70 papers · 863 · h-index 18

Impact in

Papers in

    • Machine Learning in Bioinformatics 8
    • Bioinformatics and Genomic Networks 8
    • Single-cell and spatial transcriptomics 7
    • Circular RNAs in diseases 6
    • RNA modifications and cancer 6
    • Cancer-related molecular mechanisms research 15
    • MicroRNA in disease regulation 9

Zejun Li

64 papers receiving 842 citations

Peers

Zejun Li
Comparison fields: 5 of 129
  • Cancer Research 268
  • Computational Theory and Mathematics 109
  • Molecular Biology 441
  • Biophysics 21
  • Ecological Modeling 15
Replace Michael M. Hoffman with:
Michael M. Hoffman Canada
Anna Gambin Poland
Chen‐An Tsai Taiwan
Maria Secrier United Kingdom
Arda Halu United States
Paola Lecca Italy
Li Wen China
Qizhai Li China
Erik Schultes Netherlands
Zejun Li relative to Michael M. Hoffman Canada Michael M. Hoffman's profile →
Citations per field
00.5×1.5×2.5×
Michael M. Hoffman · 1×
Citations per year

Countries citing papers authored by Zejun Li

Since Specialization
Citations

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

Fields of papers citing papers by Zejun Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201755
2 201847
3 201942
4 202337
5 201837
6 201237
7 202137
8 202332
9 201829
10 201227
11 201926
12 202324
13 202224
14 202223
15 202223
16 201622
17 201222
18 201219
19 201817
20 202117

About Zejun Li

Zejun Li is a scholar working on Molecular Biology, Cancer Research, Biomedical Engineering, Computational Theory and Mathematics and Artificial Intelligence, having authored 70 papers that have together received 863 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (15 papers), MicroRNA in disease regulation (9 papers), Machine Learning in Bioinformatics (8 papers), Computational Drug Discovery Methods (8 papers), Bioinformatics and Genomic Networks (8 papers), Single-cell and spatial transcriptomics (7 papers), Circular RNAs in diseases (6 papers) and RNA modifications and cancer (6 papers). The work is most often cited by research in Cancer Research (268 citations), Computational Theory and Mathematics (109 citations), Molecular Biology (441 citations), Biophysics (21 citations) and Ecological Modeling (15 citations). Zejun Li has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Lihong Peng, Min Chen, Bo Liao, Jialiang Yang, Lijun Cai, Xing Chen, Bo Liao, Haihua Liu, Peng Wang and Taiwei Chu. Their work appears in journals such as Frontiers in Microbiology, Scientific Reports, Computers in Biology and Medicine, IEEE Journal of Biomedical and Health Informatics and Mathematical Biosciences & Engineering.

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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