Catherine A. Reardon

10.3k citations
132 papers · 7.7k indexed · 3 hit papers · h-index 47
Topics
Atherosclerosis and Cardiovascular Diseases (36 papers)Cholesterol and Lipid Metabolism (35 papers)Peroxisome Proliferator-Activated Receptors (28 papers)

In The Last Decade

Catherine A. Reardon

130 papers receiving 7.6k citations

Hit Papers

Animal Models of Atherosclerosis2012202620162021201220182021100200300400

Peers

Catherine A. Reardon
Comparison fields: 5 of 142
  • Molecular Biology 2.9k
  • Surgery 2.1k
  • Immunology 2.0k
  • Physiology 1.9k
  • Epidemiology 1.3k
Replace János G. Filep with:
János G. Filep Canada
Ákos Heinemann Austria
Derek A. Mann United Kingdom
Lawrence Chan United States
Wim Martinet Belgium
Marten H. Hofker Netherlands
Alyssa H. Hasty United States
Karin Bornfeldt United States
Ann–Hwee Lee United States
Yury I. Miller United States
Catherine A. Reardon relative to János G. Filep Canada János G. Filep's profile →
Citations per field
00.5×1.5×2.1×
János G. Filep · 1×
Citations per year

Countries citing papers authored by Catherine A. Reardon

Since Specialization
Citations

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

Fields of papers citing papers by Catherine A. Reardon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Catherine A. Reardon. 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 Catherine A. Reardon. The network helps show where Catherine A. Reardon may publish in the future.

Co-authorship network of co-authors of Catherine A. Reardon

This figure shows the co-authorship network connecting the top 25 collaborators of Catherine A. Reardon. A scholar is included among the top collaborators of Catherine A. Reardon based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Catherine A. Reardon. Catherine A. Reardon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 83
2 71
3 36
4 76
5 15
6 61
7 1
8 9
9 28
10 91
11 28
12 58
13 55
14 52
15 1
16
Novel proteasome inhibitors show potent anti-tumor efficacy
1
17 18
18 61
19 4
20 9

About Catherine A. Reardon

Catherine A. Reardon is a scholar working on Immunology, Surgery and Endocrinology, Diabetes and Metabolism, having authored 132 papers that have together received 7.7k indexed citations. Recurring topics across this work include Atherosclerosis and Cardiovascular Diseases (36 papers), Cholesterol and Lipid Metabolism (35 papers) and Peroxisome Proliferator-Activated Receptors (28 papers). The work is most often cited by research in Immunology (2.0k citations), Physiology (1.9k citations) and Endocrinology, Diabetes and Metabolism (903 citations). Catherine A. Reardon has collaborated with scholars based in United States, China and Austria. Frequent co-authors include Godfrey S. Getz, Paul A. VanderLaan, Mary Jo LaDu, John R. Lukens, Veneracion G. Cabana, John M. Taylor, T Mazzone, Timothy J. Sontag, Geoffrey D. Wool and Linda J. Van Eldik. Their work appears in journals such as Science, Cell and Proceedings of the National Academy of Sciences.

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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