Changjun Wu

2.3k citations
8 papers · 125 · h-index 5

Impact in

    • Insect-Plant Interactions and Control
    • Plant Virus Research Studies
    • Plant-Microbe Interactions and Immunity

Papers in

    • Genomics and Phylogenetic Studies 5
    • Bioinformatics and Genomic Networks 3
    • Gene expression and cancer classification 2
    • Machine Learning in Bioinformatics 2
    • Algorithms and Data Compression 2

Changjun Wu

8 papers receiving 120 citations

Peers

Changjun Wu
Comparison fields: 5 of 21
  • Insect Science 34
  • Plant Science 62
  • Molecular Biology 45
  • Genetics 18
  • Hardware and Architecture 4
Replace Zhenfei Hu with:
Zhenfei Hu China
Rachel Hillmer United States
Xinying Guo China
Ivelina Nikolova Bulgaria
Jean‐Sébastien Légaré Canada
Martin D. Muggli United States
Ted Slater United States
Yves Sucaet United States
M. Ganesh India
Changjun Wu relative to Zhenfei Hu China Zhenfei Hu's profile →
Citations per field
00.5×1.5×
Zhenfei Hu · 1×
Citations per year

Countries citing papers authored by Changjun Wu

Since Specialization
Citations

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

Fields of papers citing papers by Changjun Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 11 scholars most cited alongside Changjun Wu, 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 Changjun Wu Line = papers co-authored together Changjun Wu links everyone, so they are left out of the graph.

All Works

About Changjun Wu

Changjun Wu is a scholar working on Molecular Biology, Artificial Intelligence, Information Systems, Statistical and Nonlinear Physics and Ecology, having authored 8 papers that have together received 125 indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (5 papers), Bioinformatics and Genomic Networks (3 papers), Web Data Mining and Analysis (2 papers), Gene expression and cancer classification (2 papers), Algorithms and Data Compression (2 papers), Machine Learning in Bioinformatics (2 papers), Data Management and Algorithms (1 paper) and Microbial Community Ecology and Physiology (1 paper). The work is most often cited by research in Insect Science (34 citations), Plant Science (62 citations), Molecular Biology (45 citations), Genetics (18 citations) and Hardware and Architecture (4 citations). Changjun Wu has collaborated with scholars based in United States and China. Frequent co-authors include Ananth Kalyanaraman, William R. Cannon, Changju Yang, Hongxia Hua, Yuqing He, Guanjun Gao, Jie Hu, Jinghua Xiao, Xin Li and Ananth Kalyanaraman. Their work appears in journals such as Molecular Breeding, IEEE Transactions on Parallel and Distributed Systems and IEEE International Conference on High Performance Computing, Data, and Analytics.

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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