Lesong Wei

710 citations
13 papers · 383 · h-index 9

Impact in

Papers in

    • Machine Learning in Bioinformatics 6
    • vaccines and immunoinformatics approaches 6
    • Biochemical and Structural Characterization 3
    • Protein Structure and Dynamics 3
    • RNA and protein synthesis mechanisms 2
    • Chemical Synthesis and Analysis 2
    • Computational Drug Discovery Methods 6

Lesong Wei

13 papers receiving 380 citations

Peers

Lesong Wei
Comparison fields: 5 of 54
  • Microbiology 89
  • Computational Theory and Mathematics 129
  • Molecular Biology 338
  • Biophysics 5
  • Immunology 18
Replace Bilal Nizami with:
Bilal Nizami South Africa
Tadakazu Takakura Japan
Zengchao Mu China
Ya-Wei Zhao China
Lantian Yao China
En-Ze Deng China
Chengfei Yan United States
Weiliang Zhu China
Dmitrii Nechaev Germany
Lesong Wei relative to Bilal Nizami South Africa Bilal Nizami's profile →
Citations per field
00.5×4.3×
Bilal Nizami · 1×
Citations per year

Countries citing papers authored by Lesong Wei

Since Specialization
Citations

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

Fields of papers citing papers by Lesong Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

13 of 13 papers shown
#Work
1 2022111
2 202181
3 202347
4 202237
5 202236
6 202220
7 202118
8 202113
9 20229
10 20245
11 20213
12 20222
13 20251

About Lesong Wei

Lesong Wei is a scholar working on Molecular Biology, Computational Theory and Mathematics, Microbiology, Materials Chemistry and Infectious Diseases, having authored 13 papers that have together received 383 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (6 papers), Computational Drug Discovery Methods (6 papers), vaccines and immunoinformatics approaches (6 papers), Antimicrobial Peptides and Activities (4 papers), Biochemical and Structural Characterization (3 papers), Protein Structure and Dynamics (3 papers), RNA and protein synthesis mechanisms (2 papers) and Chemical Synthesis and Analysis (2 papers). The work is most often cited by research in Microbiology (89 citations), Computational Theory and Mathematics (129 citations), Molecular Biology (338 citations), Biophysics (5 citations) and Immunology (18 citations). Lesong Wei has collaborated with scholars based in China, Japan and South Korea. Frequent co-authors include Leyi Wei, Xiucai Ye, Tetsuya Sakurai, Zengchao Mu, Yi Jiang, Jie Chen, Yitian Fang, Dong‐Qing Wei, Lizhen Cui and Kai Zhang. Their work appears in journals such as Briefings in Bioinformatics, Methods, Bioinformatics, Computers in Biology and Medicine and BMC Biology.

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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