Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
An Antidiabetic Thiazolidinedione Is a High Affinity Ligand for Peroxisome Proliferator-activated Receptor γ (PPARγ)
19953.1k citationsJürgen M. Lehmann, Linda B. Moore et al.Journal of Biological Chemistryprofile →
Bile Acids: Natural Ligands for an Orphan Nuclear Receptor
19991.9k citationsDerek J. Parks, Steven G. Blanchard et al.profile →
Fatty acids and eicosanoids regulate gene expression through direct interactions with peroxisome proliferator-activated receptors α and γ
19971.8k citationsSteven A. Kliewer, Scott S. Sundseth et al.profile →
A prostaglandin J2 metabolite binds peroxisome proliferator-activated receptor γ and promotes adipocyte differentiation
19951.8k citationsSteven A. Kliewer, Timothy M. Willson et al.Cellprofile →
An Orphan Nuclear Receptor Activated by Pregnanes Defines a Novel Steroid Signaling Pathway
19981.3k citationsSteven A. Kliewer, John T. Moore et al.Cellprofile →
Activation of the Nuclear Receptor LXR by Oxysterols Defines a New Hormone Response Pathway
19971.0k citationsJürgen M. Lehmann, Steven A. Kliewer et al.Journal of Biological Chemistryprofile →
Peroxisome Proliferator-activated Receptors α and γ Are Activated by Indomethacin and Other Non-steroidal Anti-inflammatory Drugs
1997960 citationsJürgen M. Lehmann, James M. Lenhard et al.Journal of Biological Chemistryprofile →
Molecular Recognition of Fatty Acids by Peroxisome Proliferator–Activated Receptors
1999938 citationsH. Eric Xu, Millard H. Lambert et al.Molecular Cellprofile →
The Structure−Activity Relationship between Peroxisome Proliferator-Activated Receptor γ Agonism and the Antihyperglycemic Activity of Thiazolidinediones
1996569 citationsTimothy M. Willson, Jeffery E. Cobb et al.Journal of Medicinal Chemistryprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Jürgen M. Lehmann
Since
Specialization
Citations
This map shows the geographic impact of Jürgen M. Lehmann'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 Jürgen M. Lehmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jürgen M. Lehmann more than expected).
Fields of papers citing papers by Jürgen M. Lehmann
This network shows the impact of papers produced by Jürgen M. Lehmann. 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 Jürgen M. Lehmann. The network helps show where Jürgen M. Lehmann may publish in the future.
Co-authorship network of co-authors of Jürgen M. Lehmann
This figure shows the co-authorship network connecting the top 25 collaborators of Jürgen M. Lehmann.
A scholar is included among the top collaborators of Jürgen M. Lehmann 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 Jürgen M. Lehmann. Jürgen M. Lehmann is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Xu, H. Eric, Millard H. Lambert, Valerie G. Montana, et al.. (1999). Molecular Recognition of Fatty Acids by Peroxisome Proliferator–Activated Receptors. Molecular Cell. 3(3). 397–403.938 indexed citations breakdown →
Kliewer, Steven A., Jürgen M. Lehmann, Michael V. Milburn, & Timothy M. Willson. (1999). The PPARs and PXRs: nuclear xenobiotic receptors that define novel hormone signaling pathways.. PubMed. 54. 345–67; discussion 367.90 indexed citations
Kliewer, Steven A., John T. Moore, Jeff L. Staudinger, et al.. (1998). An Orphan Nuclear Receptor Activated by Pregnanes Defines a Novel Steroid Signaling Pathway. Cell. 92(1). 73–82.1299 indexed citations breakdown →
Lehmann, Jürgen M., Steven A. Kliewer, Linda B. Moore, et al.. (1997). Activation of the Nuclear Receptor LXR by Oxysterols Defines a New Hormone Response Pathway. Journal of Biological Chemistry. 272(6). 3137–3140.1013 indexed citations breakdown →
Lehmann, Jürgen M., et al.. (1997). Peroxisome Proliferator-activated Receptors α and γ Are Activated by Indomethacin and Other Non-steroidal Anti-inflammatory Drugs. Journal of Biological Chemistry. 272(6). 3406–3410.960 indexed citations breakdown →
11.
Willson, Timothy M., Jeffery E. Cobb, David J. Cowan, et al.. (1996). The Structure−Activity Relationship between Peroxisome Proliferator-Activated Receptor γ Agonism and the Antihyperglycemic Activity of Thiazolidinediones. Journal of Medicinal Chemistry. 39(3). 665–668.569 indexed citations breakdown →
Lehmann, Jürgen M., Linda B. Moore, Tracey Smith-Oliver, et al.. (1995). An Antidiabetic Thiazolidinedione Is a High Affinity Ligand for Peroxisome Proliferator-activated Receptor γ (PPARγ). Journal of Biological Chemistry. 270(22). 12953–12956.3145 indexed citations breakdown →
14.
Kliewer, Steven A., et al.. (1995). A prostaglandin J2 metabolite binds peroxisome proliferator-activated receptor γ and promotes adipocyte differentiation. Cell. 83(5). 813–819.1776 indexed citations breakdown →
Lehmann, Jürgen M., Marcia I. Dawson, Peter D. Hobbs, Matthias Husmann, & Magnus Pfahl. (1991). Identification of retinoids with nuclear receptor subtype-selective activities.. PubMed. 51(18). 4804–9.87 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.