Chengyang Ji

542 citations
16 papers · 316 · h-index 9

Impact in

  • Virology top 5%
    • Poxvirus research and outbreaks
    • SARS-CoV-2 and COVID-19 Research
    • COVID-19 Clinical Research Studies
    • SARS-CoV-2 detection and testing

Papers in

    • SARS-CoV-2 and COVID-19 Research 10
    • SARS-CoV-2 detection and testing 4
    • Viral gastroenteritis research and epidemiology 3
    • COVID-19 Clinical Research Studies 2
    • Genomics and Phylogenetic Studies 3
    • vaccines and immunoinformatics approaches 3

Chengyang Ji

16 papers receiving 311 citations

Peers

Chengyang Ji
Comparison fields: 5 of 49
  • Virology 126
  • Infectious Diseases 131
  • Epidemiology 93
  • Animal Science and Zoology 29
  • Modeling and Simulation 12
Replace A Ruhan with:
A Ruhan China
Daniel Bourquain Germany
Jordan Anderson-Daniels United States
Patricia Pérez Spain
Toong Seng Tan Japan
Sven Blokland Netherlands
Masanobu Kinomoto Japan
Max T. Dufford United States
Baokun Sui China
Marie-Lise Blondot France
Chengyang Ji relative to A Ruhan China A Ruhan's profile →
Citations per field
00.5×1.5×1.9×
A Ruhan · 1×
Citations per year

Countries citing papers authored by Chengyang Ji

Since Specialization
Citations

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

Fields of papers citing papers by Chengyang Ji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 2022132
2 202147
3 202028
4 202220
5 201913
6 202213
7 202113
8 201912
9 202210
10 20256
11 20235
12 20225
13 20244
14 20224
15 20223
16 20251

About Chengyang Ji

Chengyang Ji is a scholar working on Infectious Diseases, Molecular Biology, Animal Science and Zoology, Ecology and Epidemiology, having authored 16 papers that have together received 316 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (10 papers), SARS-CoV-2 detection and testing (4 papers), Genomics and Phylogenetic Studies (3 papers), Viral gastroenteritis research and epidemiology (3 papers), vaccines and immunoinformatics approaches (3 papers), Animal Virus Infections Studies (3 papers), COVID-19 Clinical Research Studies (2 papers) and Bacteriophages and microbial interactions (2 papers). The work is most often cited by research in Virology (126 citations), Infectious Diseases (131 citations), Epidemiology (93 citations), Animal Science and Zoology (29 citations) and Modeling and Simulation (12 citations). Chengyang Ji has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Aiping Wu, Jingzhe Shang, Lulan Wang, Genhong Cheng, Saba R. Aliyari, Hangyu Zhou, Na Han, Taijiao Jiang, Rong Yang and Ziyi Chen. Their work appears in journals such as Viruses, Virus Evolution, Protein & Cell, BMC Bioinformatics and Briefings in 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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