Junting Ren

483 citations
13 papers · 288 · h-index 6

Impact in

    • COVID-19 Clinical Research Studies
    • SARS-CoV-2 and COVID-19 Research
    • SARS-CoV-2 detection and testing
    • Long-Term Effects of COVID-19

Papers in

Junting Ren

12 papers receiving 283 citations

Peers

Junting Ren
Comparison fields: 5 of 71
  • Infectious Diseases 196
  • Neurology 41
  • Nutrition and Dietetics 33
  • Modeling and Simulation 9
  • Biomedical Engineering 56
Replace Yanbing Zhou with:
Yanbing Zhou China
Sabrina Bastianelli Italy
Shuntong Kang China
Chaolin Huang China
Chunbao Xie China
Dmytro Butov Ukraine
Beom Soo Kim United States
Ayesha Baig Germany
Daniella Vaskovich‐Koubi Israel
Junting Ren relative to Yanbing Zhou China Yanbing Zhou's profile →
Citations per field
00.5×4.5×
Yanbing Zhou · 1×
Citations per year

Countries citing papers authored by Junting Ren

Since Specialization
Citations

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

Fields of papers citing papers by Junting Ren

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

13 of 13 papers shown
#Work
1 2020113
2 202186
3 202132
4 201817
5 201915
6 20229
7 20235
8 20225
9 20252
10 20232
11 20241
12 20241
13 20240

About Junting Ren

Junting Ren is a scholar working on Materials Chemistry, Electrical and Electronic Engineering, Infectious Diseases, Statistics and Probability and Molecular Biology, having authored 13 papers that have together received 288 indexed citations. Recurring topics across this work include Quantum Dots Synthesis And Properties (4 papers), Chalcogenide Semiconductor Thin Films (4 papers), Copper-based nanomaterials and applications (3 papers), Long-Term Effects of COVID-19 (2 papers), Statistical Methods and Bayesian Inference (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Cancer-related molecular mechanisms research (2 papers) and Statistical Methods and Inference (2 papers). The work is most often cited by research in Infectious Diseases (196 citations), Neurology (41 citations), Nutrition and Dietetics (33 citations), Modeling and Simulation (9 citations) and Biomedical Engineering (56 citations). Junting Ren has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Karen Messer, Jingjing Zou, Lori B. Daniels, Quan M. Bui, Chris Longhurst, Amy M. Sitapati, Jing Zhang, Michael H. Criqui, Daniel McDonald and Natasha K. Martin. Their work appears in journals such as Ceramics International, Surfaces and Interfaces, Journal of Alloys and Compounds, Solar RRL and BMC Cancer.

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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