Casey S. John

451 citations
28 papers · 316 · h-index 9

Impact in

Papers in

    • Diet and metabolism studies 4
    • Adipose Tissue and Metabolism 3
    • Alzheimer's disease research and treatments 2
    • Mitochondrial Function and Pathology 4

Casey S. John

23 papers receiving 309 citations

Peers

Casey S. John
Comparison fields: 5 of 83
  • Rehabilitation 90
  • Complementary and alternative medicine 40
  • Physiology 98
  • Biochemistry 24
  • Cell Biology 38
Replace Yang Wen-ge with:
Yang Wen-ge China
Joel S. Burrill United States
Laura Blancquaert Belgium
Camila A. Sakaguchi United States
Katarzyna Kempa Poland
Rie Ishizawa Japan
Evan J.H. Lewis Canada
Brian Leutholtz United States
Nobumasa Iwanaka Japan
Danica Michaličková Czechia
Casey S. John relative to Yang Wen-ge China Yang Wen-ge's profile →
Citations per field
00.5×4.8×
Yang Wen-ge · 1×
Citations per year

Countries citing papers authored by Casey S. John

Since Specialization
Citations

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

Fields of papers citing papers by Casey S. John

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Casey S. John. 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 Casey S. John. The network helps show where Casey S. John may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201495
2 201555
3 201631
4 201928
5 202118
6 202216
7 202213
8 20248
9 20178
10 20237
11 20207
12 20205
13 20215
14 20214
15 20233
16 20173
17 20243
18 20232
19 20251
20 20221

About Casey S. John

Casey S. John is a scholar working on Physiology, Molecular Biology, Rehabilitation, Complementary and alternative medicine and Cardiology and Cardiovascular Medicine, having authored 28 papers that have together received 316 indexed citations. Recurring topics across this work include Cardiovascular and exercise physiology (4 papers), Mitochondrial Function and Pathology (4 papers), Exercise and Physiological Responses (4 papers), Diet and metabolism studies (4 papers), Muscle metabolism and nutrition (3 papers), Adipose Tissue and Metabolism (3 papers), Alzheimer's disease research and treatments (2 papers) and High Altitude and Hypoxia (2 papers). The work is most often cited by research in Rehabilitation (90 citations), Complementary and alternative medicine (40 citations), Physiology (98 citations), Biochemistry (24 citations) and Cell Biology (38 citations). Casey S. John has collaborated with scholars based in United States, New Zealand and Australia. Frequent co-authors include Kevin A. Zwetsloot, R. Andrew Shanely, Rebecca A. Battista, Marcus M. Lawrence, David C. Nieman, Mary Pat Meaney, Jill K. Morris, Wei Sha, Kirk L. Pappan and Nicholas D. Gillitt. Their work appears in journals such as Alzheimer s & Dementia, Journal of Alzheimer s Disease, Journal of Visualized Experiments, Contemporary Clinical Trials and Current Alzheimer Research.

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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