Tom Doebber

1.9k total citations · 1 hit paper
7 papers, 1.6k citations indexed

About

Tom Doebber is a scholar working on Molecular Biology, Physiology and Epidemiology. According to data from OpenAlex, Tom Doebber has authored 7 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Physiology and 2 papers in Epidemiology. Recurrent topics in Tom Doebber's work include Peroxisome Proliferator-Activated Receptors (5 papers), Adipose Tissue and Metabolism (5 papers) and Metabolism, Diabetes, and Cancer (3 papers). Tom Doebber is often cited by papers focused on Peroxisome Proliferator-Activated Receptors (5 papers), Adipose Tissue and Metabolism (5 papers) and Metabolism, Diabetes, and Cancer (3 papers). Tom Doebber collaborates with scholars based in United States and United Kingdom. Tom Doebber's co-authors include Joel P. Berger, John A. Wagner, Philipp E. Scherer, Terry P. Combs, Margaret Wu, Steven E. Kahn, Jerrold M. Olefsky, Michael W. Rajala, Thomas A. Buchanan and Meredith Hawkins and has published in prestigious journals such as Journal of Biological Chemistry, Endocrinology and European Journal of Pharmacology.

In The Last Decade

Tom Doebber

7 papers receiving 1.6k citations

Hit Papers

Complex Distribution, Not Absolute Amount of Adiponectin,... 2004 2026 2011 2018 2004 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tom Doebber United States 6 1.2k 875 483 327 301 7 1.6k
Joseph G. Yu United States 7 645 0.5× 707 0.8× 491 1.0× 185 0.6× 154 0.5× 8 1.3k
Justin Chapman United States 13 766 0.7× 716 0.8× 628 1.3× 68 0.2× 169 0.6× 19 1.8k
Federica Sentinelli Italy 20 695 0.6× 363 0.4× 300 0.6× 143 0.4× 264 0.9× 52 1.4k
Maria E. Trujillo United States 12 468 0.4× 612 0.7× 437 0.9× 87 0.3× 267 0.9× 23 1.3k
Merja Santaniemi Finland 15 502 0.4× 314 0.4× 182 0.4× 159 0.5× 197 0.7× 22 911
Stephan Francke United States 12 380 0.3× 492 0.6× 387 0.8× 378 1.2× 118 0.4× 20 1.3k
Wataru Kameda Japan 19 400 0.3× 309 0.4× 300 0.6× 124 0.4× 194 0.6× 49 1.2k
Karen SL Lam Hong Kong 14 465 0.4× 348 0.4× 621 1.3× 81 0.2× 237 0.8× 16 1.3k
Esther Guiu‐Jurado Spain 19 588 0.5× 368 0.4× 308 0.6× 81 0.2× 157 0.5× 31 1.1k
Bronwyn Atcheson Australia 7 423 0.4× 727 0.8× 681 1.4× 77 0.2× 112 0.4× 7 1.5k

Countries citing papers authored by Tom Doebber

Since Specialization
Citations

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

Fields of papers citing papers by Tom Doebber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tom Doebber. 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 Tom Doebber. The network helps show where Tom Doebber may publish in the future.

Co-authorship network of co-authors of Tom Doebber

This figure shows the co-authorship network connecting the top 25 collaborators of Tom Doebber. A scholar is included among the top collaborators of Tom Doebber 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 Tom Doebber. Tom Doebber is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

7 of 7 papers shown
1.
Chang, Ching H., Lesley A. McNamara, Margaret Wu, et al.. (2008). A novel selective peroxisome proliferator-activator receptor-γ modulator—SPPARγM5 improves insulin sensitivity with diminished adverse cardiovascular effects. European Journal of Pharmacology. 584(1). 192–201. 25 indexed citations
2.
Dropinski, James F., Taro E. Akiyama, Monica Einstein, et al.. (2005). Synthesis and biological activities of novel aryl indole-2-carboxylic acid analogs as PPARγ partial agonists. Bioorganic & Medicinal Chemistry Letters. 15(22). 5035–5038. 56 indexed citations
3.
Wagner, John A., Patrick Larson, Jutta Miller, et al.. (2005). Individual and Combined Effects of Peroxisome Proliferator‐Activated Receptor α and γ Agonists, Fenofibrate and Rosiglitazone, on Biomarkers of Lipid and Glucose Metabolism in Healthy Nondiabetic Volunteers. The Journal of Clinical Pharmacology. 45(5). 504–513. 26 indexed citations
4.
Pajvani, Utpal B., Meredith Hawkins, Terry P. Combs, et al.. (2004). Complex Distribution, Not Absolute Amount of Adiponectin, Correlates with Thiazolidinedione-mediated Improvement in Insulin Sensitivity. Journal of Biological Chemistry. 279(13). 12152–12162. 978 indexed citations breakdown →
5.
Combs, Terry P., John A. Wagner, Joel P. Berger, et al.. (2002). Induction of Adipocyte Complement-Related Protein of 30 Kilodaltons by PPARγ Agonists: A Potential Mechanism of Insulin Sensitization. Endocrinology. 143(3). 998–1007. 497 indexed citations
6.
Wang, Pei-Ran, Qiu Guo, Marc C. Ippolito, et al.. (2001). High fat fed hamster, a unique animal model for treatment of diabetic dyslipidemia with peroxisome proliferator activated receptor alpha selective agonists. European Journal of Pharmacology. 427(3). 285–293. 51 indexed citations
7.
Biftu, Tesfaye, John C. Chabala, John J. Acton, et al.. (1988). Synthesis and structure-activity relationship of 2,5-diaryltetrahydrofurans as PAF antagonists. Prostaglandins. 35(5). 846–846. 3 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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