Mackenzie Pearson

1.9k citations
18 papers · 878 · h-index 12

Impact in

    • 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 6

Mackenzie Pearson

16 papers receiving 875 citations

Peers

Mackenzie Pearson
Comparison fields: 5 of 78
  • Biochemistry 105
  • Physiology 303
  • Epidemiology 294
  • Endocrine and Autonomic Systems 56
  • Endocrinology, Diabetes and Metabolism 136
Replace Leon G. Straub with:
Leon G. Straub United States
David J. Pedersen Australia
Thomas S. Nielsen Denmark
Pratik Aryal United States
Maria Kaaman Sweden
Krishna K. Narra United States
Lena William‐Olsson Sweden
Liqun Tian United States
Alison B. Kohan United States
Alberto Distefano United States
Mackenzie Pearson relative to Leon G. Straub United States Leon G. Straub's profile →
Citations per field
00.5×2.6×
Leon G. Straub · 1×
Citations per year

Countries citing papers authored by Mackenzie Pearson

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Mackenzie Pearson Line = papers co-authored together Mackenzie Pearson links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 2015281
2 2017143
3 2014138
4 202167
5 201642
6 201737
7 201636
8 202432
9 202329
10 202025
11 202320
12 202214
13 201711
14 20201
15 20261
16 20201
17 20250
18 20250

About Mackenzie Pearson

Mackenzie Pearson is a scholar working on Molecular Biology, Physiology, Biochemistry, Endocrine and Autonomic Systems and Surgery, having authored 18 papers that have together received 878 indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (6 papers), Metabolomics and Mass Spectrometry Studies (5 papers), Lipid metabolism and biosynthesis (3 papers), Regulation of Appetite and Obesity (3 papers), Sphingolipid Metabolism and Signaling (2 papers), Mass Spectrometry Techniques and Applications (2 papers), Adipokines, Inflammation, and Metabolic Diseases (2 papers) and Pancreatic function and diabetes (2 papers). The work is most often cited by research in Biochemistry (105 citations), Physiology (303 citations), Epidemiology (294 citations), Endocrine and Autonomic Systems (56 citations) and Endocrinology, Diabetes and Metabolism (136 citations). Mackenzie Pearson has collaborated with scholars based in United States, Netherlands and Portugal. Frequent co-authors include William L. Holland, Philipp E. Scherer, Ankit X. Sharma, Jonathan Y. Xia, Kai Sun, Ruth Gordillo, Christine M. Kusminski, Jeffrey G. McDonald, Shawn C. Burgess and João Duarte. Their work appears in journals such as eLife, Cell Metabolism, The FASEB Journal, Diabetes and Journal of Lipid 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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