Mackenzie Pearson
Impact in
- Biochemistry top 5%
- Lipid metabolism and biosynthesis
- Physiology top 10%
- Adipose Tissue and Metabolism
- Diet and metabolism studies
Papers in
-
- Metabolomics and Mass Spectrometry Studies 5
- Sphingolipid Metabolism and Signaling 2
-
- Adipose Tissue and Metabolism 5
- Co-authors
- William L. Holland (6 shared papers)Ankit X. Sharma (3 shared papers)Philipp E. Scherer (3 shared papers)Jonathan Y. Xia (3 shared papers)Ruth Gordillo (2 shared papers)Kai Sun (2 shared papers)Christine M. Kusminski (2 shared papers)Jeffrey G. McDonald (1 shared paper)
- Journals
- eLife (3 papers)The FASEB Journal (2 papers)Genes & Development (1 paper)Journal of Lipid Research (1 paper)Cell Metabolism (1 paper)
- Partner nations
- United StatesNetherlandsSouth Korea
In The Last Decade
Mackenzie Pearson
14 papers receiving 806 citations
Peers
Comparison fields: 5 of 83
- Biochemistry 107
- Physiology 316
- Epidemiology 313
- Endocrine and Autonomic Systems 58
- Endocrinology, Diabetes and Metabolism 133
Countries citing papers authored by Mackenzie Pearson
This map shows the geographic impact of Mackenzie Pearson'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 Mackenzie Pearson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mackenzie Pearson more than expected).
Fields of papers citing papers by Mackenzie Pearson
This network shows the impact of papers produced by Mackenzie Pearson. 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 Mackenzie Pearson. The network helps show where Mackenzie Pearson may publish in the future.
Co-authors
The 25 scholars most cited alongside Mackenzie Pearson, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 271 | |
| 2 | 2014 | 138 | |
| 3 | 2017 | 136 | |
| 4 | 2021 | 62 | |
| 5 | 2016 | 40 | |
| 6 | 2017 | 37 | |
| 7 | 2016 | 35 | |
| 8 | 2020 | 24 | |
| 9 | 2023 | 22 | |
| 10 | 2023 | 18 | |
| 11 | 2022 | 13 | |
| 12 | 2017 | 11 | |
| 13 | 2020 | 1 | |
| 14 | 2020 | 1 |
About Mackenzie Pearson
Mackenzie Pearson is a scholar working on Molecular Biology, Physiology, Biochemistry, Spectroscopy and Cellular and Molecular Neuroscience, having authored 14 papers that have together received 809 indexed citations. Recurring topics across this work include Metabolomics and Mass Spectrometry Studies (5 papers), Adipose Tissue and Metabolism (5 papers), Lipid metabolism and biosynthesis (3 papers), Mass Spectrometry Techniques and Applications (3 papers), Sphingolipid Metabolism and Signaling (2 papers), Advanced Proteomics Techniques and Applications (2 papers), Adipokines, Inflammation, and Metabolic Diseases (2 papers) and Regulation of Appetite and Obesity (2 papers). The work is most often cited by research in Biochemistry (107 citations), Physiology (316 citations), Epidemiology (313 citations), Endocrine and Autonomic Systems (58 citations) and Endocrinology, Diabetes and Metabolism (133 citations). Mackenzie Pearson has collaborated with scholars based in United States, Netherlands and South Korea. Frequent co-authors include William L. Holland, Ankit X. Sharma, Philipp E. Scherer, Jonathan Y. Xia, Ruth Gordillo, Kai Sun, Christine M. Kusminski, Jeffrey G. McDonald, Shawn C. Burgess and John G. Jones. Their work appears in journals such as eLife, The FASEB Journal, Genes & Development, Journal of Lipid Research and Cell Metabolism.
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.