Kaida Ji

497 citations
15 papers · 429 · h-index 11

Impact in

Papers in

    • Metabolism, Diabetes, and Cancer 2
    • Angiogenesis and VEGF in Cancer 2
    • Cancer, Lipids, and Metabolism 2
    • Cancer, Hypoxia, and Metabolism 2
    • Protease and Inhibitor Mechanisms 2

Kaida Ji

15 papers receiving 426 citations

Peers

Kaida Ji
Comparison fields: 5 of 69
  • Cancer Research 87
  • Cardiology and Cardiovascular Medicine 95
  • Endocrinology, Diabetes and Metabolism 59
  • Oncology 81
  • Immunology 60
Replace Giovanna Baccante with:
Giovanna Baccante Italy
Eva Tarantino Italy
C. Adamy France
Michitaka Tsuzuki Japan
Shinsaku Matsunaga Japan
Fatima Ammarguellat France
Naveen K Somanna United States
Annie Ko United States
Rachel M. Perrin United Kingdom
Soo Hyuk Kim South Korea
Kaida Ji relative to Giovanna Baccante Italy Giovanna Baccante's profile →
Citations per field
00.5×5.9×
Giovanna Baccante · 1×
Citations per year

Countries citing papers authored by Kaida Ji

Since Specialization
Citations

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

Fields of papers citing papers by Kaida Ji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 200578
2 201560
3 201647
4 201041
5 201839
6 201638
7 201029
8 200929
9 201624
10 201611
11 201610
12 20099
13 20167
14
[Osteopontin enhances migratory ability of cultured aortic adventitial fibroblasts from spontaneously hypertensive rats].
20046
15 20171

About Kaida Ji

Kaida Ji is a scholar working on Molecular Biology, Cancer Research, Cardiology and Cardiovascular Medicine, Rheumatology and Surgery, having authored 15 papers that have together received 429 indexed citations. Recurring topics across this work include Metabolism, Diabetes, and Cancer (2 papers), Cancer, Lipids, and Metabolism (2 papers), Inflammatory Biomarkers in Disease Prognosis (2 papers), Cancer, Hypoxia, and Metabolism (2 papers), Bone and Dental Protein Studies (2 papers), Angiogenesis and VEGF in Cancer (2 papers), Protease and Inhibitor Mechanisms (2 papers) and Neutrophil, Myeloperoxidase and Oxidative Mechanisms (1 paper). The work is most often cited by research in Cancer Research (87 citations), Cardiology and Cardiovascular Medicine (95 citations), Endocrinology, Diabetes and Metabolism (59 citations), Oncology (81 citations) and Immunology (60 citations). Kaida Ji has collaborated with scholars based in China and United States. Frequent co-authors include Pingjin Gao, Yan Chen, Dingliang Zhu, Wenquan Niu, Dingliang Zhu, Yi Zhang, Bradford C. Berk, Weili Shen, Ming Yin and Feng Peng. Their work appears in journals such as Biochemical and Biophysical Research Communications, Journal of Hypertension, EBioMedicine, Frontiers in Genetics and Arteriosclerosis Thrombosis and Vascular 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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