Scott Matthew Ebert

34 papers receiving 1.8k citations

Peers

Scott Matthew Ebert
Comparison fields: 5 of 109
  • Aging 59
  • Rehabilitation 157
  • Cell Biology 368
  • Geriatrics and Gerontology 73
  • Physiology 549
Replace Yun Chau Long with:
Yun Chau Long Sweden
Huiyun Liang United States
Shylesh Bhaskaran United States
Matthew D. Lynes United States
Ramzi J. Khairallah United States
Leonardo Nogueira United States
Manju Kumari India
Dipanjan Chanda South Korea
Teruhiko Shimokawa Japan
Yewei Liu United States
Scott Matthew Ebert relative to Yun Chau Long Sweden Yun Chau Long's profile →
Citations per field
00.5×1.5×1.9×
Yun Chau Long · 1×
Citations per year

Countries citing papers authored by Scott Matthew Ebert

Since Specialization
Citations

This map shows the geographic impact of Scott Matthew 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 Matthew 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 Matthew Ebert more than expected).

Fields of papers citing papers by Scott Matthew Ebert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011291
2 2012192
3 2012181
4 2013116
5 2014113
6 2010112
7 2015101
8 201497
9 201680
10 201969
11 202057
12 201449
13 202146
14 201642
15 201037
16 201735
17 202135
18 201934
19 200827
20 202326

About Scott Matthew Ebert

Scott Matthew Ebert is a scholar working on Molecular Biology, Physiology, Cardiology and Cardiovascular Medicine, Cell Biology and Cellular and Molecular Neuroscience, having authored 35 papers that have together received 1.9k 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), Genetic Neurodegenerative Diseases (5 papers), Muscle metabolism and nutrition (4 papers), Antimicrobial agents and applications (3 papers), Nuclear Structure and Function (2 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). The work is most often cited by research in Aging (59 citations), Rehabilitation (157 citations), Cell Biology (368 citations), Geriatrics and Gerontology (73 citations) and Physiology (549 citations). Scott Matthew Ebert has collaborated with scholars based in United States, Germany and France. Frequent co-authors include Christopher M. Adams, Kale S. Bongers, Daniel K. Fox, Steven D. Kunkel, Michael C. Dyle, Steven A. Bullard, Jason M. Dierdorff, Manish Suneja, Richard K. Shields and Fariborz Alipour. Their work appears in journals such as Journal of Biological Chemistry, American Journal of Physiology-Endocrinology and Metabolism, The FASEB Journal, Current Opinion in Clinical Nutrition & Metabolic Care and GeroScience.

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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