Jin Ju

750 citations
16 papers · 613 · h-index 7

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
    • Inflammasome and immune disorders
    • Circular RNAs in diseases
    • RNA modifications and cancer

Papers in

    • MicroRNA in disease regulation 4
    • Cancer Genomics and Diagnostics 2
    • Cancer-related molecular mechanisms research 2
    • Circular RNAs in diseases 2

Jin Ju

14 papers receiving 610 citations

Peers

Jin Ju
Comparison fields: 5 of 81
  • Cancer Research 220
  • Molecular Biology 391
  • Nephrology 35
  • Endocrine and Autonomic Systems 29
  • Immunology 66
Replace Shixing Ma with:
Shixing Ma China
Yuanji Ma China
Bowen Li China
Enikő Balogh Hungary
Elizabeth Rendina-Ruedy United States
Danielle L. Michell United States
Lefeng Wang China
Mary Van Demark United States
Qilan Ning China
Jin Ju relative to Shixing Ma China Shixing Ma's profile →
Citations per field
00.5×2.6×
Shixing Ma · 1×
Citations per year

Countries citing papers authored by Jin Ju

Since Specialization
Citations

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

Fields of papers citing papers by Jin Ju

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 2017353
2 201499
3 201650
4 201647
5 201917
6 202016
7 202412
8 20214
9 20194
10 20214
11 20142
12 20142
13 20172
14 20141
15 20230
16 20130

About Jin Ju

Jin Ju is a scholar working on Cancer Research, Molecular Biology, Computational Mechanics, Pulmonary and Respiratory Medicine and Mechanics of Materials, having authored 16 papers that have together received 613 indexed citations. Recurring topics across this work include MicroRNA in disease regulation (4 papers), Metallurgy and Material Forming (3 papers), Laser and Thermal Forming Techniques (3 papers), Metal Forming Simulation Techniques (3 papers), Cancer Genomics and Diagnostics (2 papers), Circular RNAs in diseases (2 papers), Advanced Numerical Analysis Techniques (2 papers) and Cancer-related molecular mechanisms research (2 papers). The work is most often cited by research in Cancer Research (220 citations), Molecular Biology (391 citations), Nephrology (35 citations), Endocrine and Autonomic Systems (29 citations) and Immunology (66 citations). Jin Ju has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Yong Zhang, Chaoqian Xu, Zhange Li, Benzhi Cai, Ranchen Xu, Baofeng Yang, Xin Liu, Lin Yuan, Jiamin Li and Xue Bai. Their work appears in journals such as Journal of Clinical Oncology, Acta Biochimica et Biophysica Sinica, Journal of Pineal Research, Biomedicine & Pharmacotherapy and Journal of Molecular and Cellular Cardiology.

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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