Junyi Li

2.5k citations
112 papers · 1.4k · h-index 21

Impact in

Papers in

    • Bioinformatics and Genomic Networks 15
    • Gene expression and cancer classification 12
    • Genomics and Phylogenetic Studies 11
    • Machine Learning in Bioinformatics 11
    • RNA modifications and cancer 6
    • Topic Modeling 9
    • Natural Language Processing Techniques 7

Junyi Li

102 papers receiving 1.4k citations

Peers

Junyi Li
Comparison fields: 5 of 155
  • Aquatic Science 119
  • Immunology 215
  • Artificial Intelligence 271
  • Computational Theory and Mathematics 115
  • Molecular Biology 465
Replace Jie Pan with:
Jie Pan China
Jie Peng China
Shu‐Yu Lin Taiwan
Tomohiro Yoshikawa Japan
Xiaodong Zhao China
Juntao Li China
Shousheng Liu China
Jiyang Dong China
Di Peng China
Seiya Imoto Japan
Junyi Li relative to Jie Pan China Jie Pan's profile →
Citations per field
00.5×3.5×
Jie Pan · 1×
Citations per year

Countries citing papers authored by Junyi Li

Since Specialization
Citations

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

Fields of papers citing papers by Junyi Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 112 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996165
2 202166
3 201964
4 201460
5 202052
6 199849
7 201538
8 201936
9 202133
10 201929
11 201828
12 202228
13 202228
14 201928
15 202228
16 202226
17 202324
18 202022
19 202021
20 202321

About Junyi Li

Junyi Li is a scholar working on Molecular Biology, Artificial Intelligence, Immunology, Cancer Research and Computer Vision and Pattern Recognition, having authored 112 papers that have together received 1.4k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (15 papers), Gene expression and cancer classification (12 papers), Genomics and Phylogenetic Studies (11 papers), Machine Learning in Bioinformatics (11 papers), Topic Modeling (9 papers), Natural Language Processing Techniques (7 papers), Cancer-related molecular mechanisms research (7 papers) and RNA modifications and cancer (6 papers). The work is most often cited by research in Aquatic Science (119 citations), Immunology (215 citations), Artificial Intelligence (271 citations), Computational Theory and Mathematics (115 citations) and Molecular Biology (465 citations). Junyi Li has collaborated with scholars based in China, United States and Switzerland. Frequent co-authors include Allan R. Brasier, Yadong Wang, R. Russell Rhinehart, Jixing Zou, Lanfen Fan, Ji-Rong Wen, Wayne Xin Zhao, Zhenlu Wang, Ani Nenkova and Tianyi Tang. Their work appears in journals such as IEEE/ACM Transactions on Computational Biology and Bioinformatics, Bioinformatics, Fish & Shellfish Immunology, Computational and Structural Biotechnology Journal and BMC Bioinformatics.

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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