Jonathan D. Smith

40.9k total citations · 13 hit papers
272 papers, 25.2k citations indexed

About

Jonathan D. Smith is a scholar working on Molecular Biology, Surgery and Immunology. According to data from OpenAlex, Jonathan D. Smith has authored 272 papers receiving a total of 25.2k indexed citations (citations by other indexed papers that have themselves been cited), including 117 papers in Molecular Biology, 74 papers in Surgery and 48 papers in Immunology. Recurrent topics in Jonathan D. Smith's work include Cholesterol and Lipid Metabolism (43 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (34 papers) and Atherosclerosis and Cardiovascular Diseases (32 papers). Jonathan D. Smith is often cited by papers focused on Cholesterol and Lipid Metabolism (43 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (34 papers) and Atherosclerosis and Cardiovascular Diseases (32 papers). Jonathan D. Smith collaborates with scholars based in United States, United Kingdom and Germany. Jonathan D. Smith's co-authors include Stanley L. Hazen, Jan L. Breslow, Masaaki Miyata, Kripa K. Varanasi, Joseph A. DiDonato, Xiaoming Fu, Tony Hayek, Zeneng Wang, W.H. Wilson Tang and Yuping Wu and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Jonathan D. Smith

267 papers receiving 24.8k citations

Hit Papers

Gut flora metabolism of phosphatidylc... 1992 2026 2003 2014 2011 1992 2012 2000 1996 1000 2.0k 3.0k 4.0k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jonathan D. Smith United States 71 9.9k 5.8k 5.3k 4.1k 3.5k 272 25.2k
Shu Chien United States 117 16.0k 1.6× 6.6k 1.1× 8.9k 1.7× 3.6k 0.9× 1.3k 0.4× 642 47.2k
Karlheinz Peter Australia 73 4.8k 0.5× 3.2k 0.6× 1.9k 0.4× 2.8k 0.7× 650 0.2× 537 19.6k
Martin L. Yarmush United States 86 9.1k 0.9× 10.0k 1.7× 1.6k 0.3× 1.4k 0.3× 939 0.3× 633 31.7k
John W. Eaton United States 80 8.9k 0.9× 1.6k 0.3× 3.3k 0.6× 1.8k 0.4× 444 0.1× 271 24.3k
Jeremy N. Skepper United Kingdom 76 7.5k 0.8× 2.1k 0.4× 2.0k 0.4× 2.8k 0.7× 610 0.2× 229 21.2k
Michael A. Gimbrone United States 103 16.2k 1.6× 6.4k 1.1× 4.8k 0.9× 12.9k 3.2× 1.3k 0.4× 185 42.7k
Asrar B. Malik United States 108 17.2k 1.7× 3.5k 0.6× 6.6k 1.2× 8.4k 2.1× 736 0.2× 582 40.5k
Richard Lee United States 102 16.8k 1.7× 10.2k 1.7× 3.5k 0.7× 5.2k 1.3× 791 0.2× 412 37.9k
John P. Cooke United States 101 11.2k 1.1× 7.3k 1.3× 11.8k 2.2× 2.9k 0.7× 2.3k 0.6× 510 35.6k
Jan Greve Netherlands 72 4.8k 0.5× 3.7k 0.6× 2.3k 0.4× 835 0.2× 801 0.2× 469 18.5k

Countries citing papers authored by Jonathan D. Smith

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan D. Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan D. Smith. 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 Jonathan D. Smith. The network helps show where Jonathan D. Smith may publish in the future.

Co-authorship network of co-authors of Jonathan D. Smith

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan D. Smith. A scholar is included among the top collaborators of Jonathan D. Smith 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 Jonathan D. Smith. Jonathan D. Smith 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
1.
Bazeley, Peter, et al.. (2025). Optimized Method to Generate Well-Characterized Macrophages from Induced Pluripotent Stem Cells. Biomedicines. 13(1). 99–99. 1 indexed citations
2.
Brubaker, Gregory, et al.. (2025). ATP8B1 regulates PIP2 localization and cleavage of pyroptotic executioner Gasdermin D. Proceedings of the National Academy of Sciences. 122(22). e2502798122–e2502798122. 1 indexed citations
3.
Wagoner, David R. Van, et al.. (2024). Transcriptomic Insights into the Atrial Fibrillation Susceptibility Locus near the MYOZ1 and SYNPO2L Genes. International Journal of Molecular Sciences. 25(19). 10309–10309. 3 indexed citations
4.
Didichenko, Svetlana A., Elena Velkoska, Alexei Navdaev, et al.. (2023). CSL112 Infusion Rapidly Increases APOA1 Exchange Rate via Specific Serum Amyloid-Poor HDL Subpopulations When Administered to Patients Post–Myocardial Infarction. Arteriosclerosis Thrombosis and Vascular Biology. 43(6). 855–869. 9 indexed citations
6.
Smith, Jonathan D., et al.. (2022). HDL Is Not Dead Yet. Biomedicines. 10(1). 128–128. 8 indexed citations
7.
Baker, Claire, et al.. (2022). The Molecular Medicine PhD program alumni perceptions of career preparedness. PLoS ONE. 17(11). e0275996–e0275996. 1 indexed citations
8.
Robinet, Peggy, et al.. (2021). Quantitative trait locus mapping identifies the Gpnmb gene as a modifier of mouse macrophage lysosome function. Scientific Reports. 11(1). 10249–10249. 12 indexed citations
9.
10.
Rennison, Julie H., Ling Li, Laurie Castel, et al.. (2021). Atrial fibrillation rhythm is associated with marked changes in metabolic and myofibrillar protein expression in left atrial appendage. Pflügers Archiv - European Journal of Physiology. 473(3). 461–475. 16 indexed citations
11.
Brubaker, Gregory, Jennifer Major, Chase Neumann, et al.. (2020). Uptake of high-density lipoprotein by scavenger receptor class B type 1 is associated with prostate cancer proliferation and tumor progression in mice. Journal of Biological Chemistry. 295(24). 8252–8261. 31 indexed citations
12.
Chung, Mina K., Sadashiva S. Karnik, Cornelia C. Bergmann, et al.. (2020). SARS-CoV-2 and ACE2: The biology and clinical data settling the ARB and ACEI controversy. EBioMedicine. 58. 102907–102907. 96 indexed citations
13.
Cui, Kui, Mitali Das, Kathleen Brown, et al.. (2017). The Upregulation of Integrin αDβ2 (CD11d/CD18) on Inflammatory Macrophages Promotes Macrophage Retention in Vascular Lesions and Development of Atherosclerosis. The Journal of Immunology. 198(12). 4855–4867. 55 indexed citations
14.
Xia, Guoxing, et al.. (2017). Dual-gratings with a Bragg reflector for dielectric laser-driven accelerators. Physics of Plasmas. 24(7). 10 indexed citations
15.
Galvani, Sylvain, Marie Sanson, Victoria A. Blaho, et al.. (2015). HDL-bound sphingosine 1-phosphate acts as a biased agonist for the endothelial cell receptor S1P 1 to limit vascular inflammation. Science Signaling. 8(389). ra79–ra79. 252 indexed citations
16.
Mete, Ö., et al.. (2015). Design studies and commissioning plans for plasma acceleration research station experimental program. Physics of Plasmas. 22(10). 1 indexed citations
17.
Lee, Byron, Peggy Robinet, Jonathan D. Smith, et al.. (2012). Dysregulation of Cholesterol Homeostasis in Human Prostate Cancer through Loss of ABCA1. Cancer Research. 73(3). 1211–1218. 124 indexed citations
18.
Chung, Mina K., John Barnard, Peter Hanna, et al.. (2011). Abstract 8221: Cis Regulation of Genes in Human Atria Near SNPs Associated with Atrial Fibrillation and PR Interval. Circulation. 124(suppl_21). 1 indexed citations
19.
Smith, Jonathan D.. (2003). Quantitative trait locus mapping for atherosclerosis susceptibility. Current Opinion in Lipidology. 14(5). 499–504. 9 indexed citations
20.
Brown, Matthew L., Jonathan D. Smith, Renee Leboeuf, et al.. (2002). The murine macrophage apoB-48 receptor gene (Apob-48r)homology to the human receptor. Journal of Lipid Research. 43(8). 1181–1191. 15 indexed citations

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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