Scott M. Ebert

33 papers receiving 1.8k citations

Peers

Scott M. Ebert
Comparison fields: 5 of 109
  • Aging 57
  • Rehabilitation 154
  • Geriatrics and Gerontology 74
  • Physiology 537
  • Cell Biology 359
Replace Yun Chau Long with:
Yun Chau Long Singapore
Shylesh Bhaskaran United States
Huiyun Liang United States
Leonardo Nogueira United States
Teruhiko Shimokawa Japan
Ramzi J. Khairallah United States
Carol Davis United States
Manju Kumari India
Daniele Lettieri‐Barbato Italy
Alexandre Prola France
Scott M. Ebert relative to Yun Chau Long Singapore Yun Chau Long's profile →
Citations per field
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Citations per year

Countries citing papers authored by Scott M. Ebert

Since Specialization
Citations

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

Fields of papers citing papers by Scott M. Ebert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Scott M. Ebert. 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 Scott M. Ebert. The network helps show where Scott M. Ebert may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011286
2 2012189
3 2012175
4 2013113
5 2014109
6 2010107
7 201596
8 201494
9 201677
10 201966
11 202053
12 201447
13 202140
14 201640
15 201037
16 201736
17 202133
18 201932
19 200827
20 202324

About Scott M. Ebert

Scott M. Ebert is a scholar working on Molecular Biology, Physiology, Cardiology and Cardiovascular Medicine, Cell Biology and Cellular and Molecular Neuroscience, having authored 34 papers that have together received 1.8k indexed citations. Recurring topics across this work include Muscle Physiology and Disorders (24 papers), Adipose Tissue and Metabolism (8 papers), Cardiomyopathy and Myosin Studies (7 papers), Muscle metabolism and nutrition (4 papers), Genetic Neurodegenerative Diseases (4 papers), Antimicrobial agents and applications (3 papers), Antimicrobial Peptides and Activities (2 papers) and Muscle activation and electromyography studies (2 papers). The work is most often cited by research in Aging (57 citations), Rehabilitation (154 citations), Geriatrics and Gerontology (74 citations), Physiology (537 citations) and Cell Biology (359 citations). Scott M. Ebert has collaborated with scholars based in United States, Germany and France. Frequent co-authors include Christopher M. Adams, Daniel K. Fox, Kale S. Bongers, Michael C. Dyle, Steven D. Kunkel, Steven A. Bullard, Jason M. Dierdorff, Manish Suneja, Fariborz Alipour and Richard K. Shields. Their work appears in journals such as Journal of Biological Chemistry, American Journal of Physiology-Endocrinology and Metabolism, The FASEB Journal, GeroScience and Current Opinion in Clinical Nutrition & Metabolic Care.

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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