Marc C. Ippolito

1.0k total citations · 1 hit paper
7 papers, 809 citations indexed

About

Marc C. Ippolito is a scholar working on Molecular Biology, Surgery and Epidemiology. According to data from OpenAlex, Marc C. Ippolito has authored 7 papers receiving a total of 809 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 3 papers in Surgery and 2 papers in Epidemiology. Recurrent topics in Marc C. Ippolito's work include Peroxisome Proliferator-Activated Receptors (6 papers), Metabolism, Diabetes, and Cancer (4 papers) and Cholesterol and Lipid Metabolism (2 papers). Marc C. Ippolito is often cited by papers focused on Peroxisome Proliferator-Activated Receptors (6 papers), Metabolism, Diabetes, and Cancer (4 papers) and Cholesterol and Lipid Metabolism (2 papers). Marc C. Ippolito collaborates with scholars based in United States and Germany. Marc C. Ippolito's co-authors include Samuel D. Wright, Xiaodong Gan, Jeremy G. Richman, Ning Ren, Tian‐Quan Cai, Stefan Offermanns, Daniel T. Connolly, Chen Liaw, Lan Jin and M. Gerard Waters and has published in prestigious journals such as Journal of Biological Chemistry, Biochemical and Biophysical Research Communications and Journal of Medicinal Chemistry.

In The Last Decade

Marc C. Ippolito

7 papers receiving 787 citations

Hit Papers

(d)-β-Hydroxybutyrate Inhibits Adipocyte Lipolysis via th... 2005 2026 2012 2019 2005 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marc C. Ippolito United States 7 402 380 221 143 95 7 809
Tsuei-Ju Wu United States 8 368 0.9× 403 1.1× 246 1.1× 186 1.3× 132 1.4× 8 1.0k
Faiyaz Ahmad India 12 281 0.7× 159 0.4× 158 0.7× 132 0.9× 79 0.8× 34 637
Diane M. Hargrove United States 17 346 0.9× 157 0.4× 223 1.0× 169 1.2× 54 0.6× 29 792
Jennifer J. Hsiao United States 9 318 0.8× 344 0.9× 154 0.7× 132 0.9× 229 2.4× 9 813
Franck Rencurel France 12 355 0.9× 165 0.4× 229 1.0× 200 1.4× 79 0.8× 12 737
Alessandra Munarini Italy 17 340 0.8× 144 0.4× 101 0.5× 120 0.8× 90 0.9× 26 939
Anna E. Marley United Kingdom 13 831 2.1× 397 1.0× 230 1.0× 424 3.0× 140 1.5× 15 1.1k
Carrie-Lynn M. Soltys Canada 15 864 2.1× 399 1.1× 115 0.5× 224 1.6× 163 1.7× 21 1.3k
Yves Mugabo Canada 12 289 0.7× 189 0.5× 168 0.8× 293 2.0× 105 1.1× 16 674
Caterina Constantinou Greece 16 287 0.7× 139 0.4× 170 0.8× 103 0.7× 78 0.8× 32 636

Countries citing papers authored by Marc C. Ippolito

Since Specialization
Citations

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

Fields of papers citing papers by Marc C. Ippolito

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marc C. Ippolito. 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 Marc C. Ippolito. The network helps show where Marc C. Ippolito may publish in the future.

Co-authorship network of co-authors of Marc C. Ippolito

This figure shows the co-authorship network connecting the top 25 collaborators of Marc C. Ippolito. A scholar is included among the top collaborators of Marc C. Ippolito 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 Marc C. Ippolito. Marc C. Ippolito 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.
Koyama, Hiroo, Daniel J. Miller, Joel P. Berger, et al.. (2005). (2R)-2-Methylchromane-2-carboxylic acids: Discovery of selective PPARα agonists as hypolipidemic agents. Bioorganic & Medicinal Chemistry Letters. 15(14). 3347–3351. 15 indexed citations
2.
Taggart, Andrew K.P., Jukka Kero, Xiaodong Gan, et al.. (2005). (d)-β-Hydroxybutyrate Inhibits Adipocyte Lipolysis via the Nicotinic Acid Receptor PUMA-G. Journal of Biological Chemistry. 280(29). 26649–26652. 529 indexed citations breakdown →
3.
Doebber, Thomas W., Linda Kelly, Gaochao Zhou, et al.. (2004). MK-0767, a novel dual PPARα/γ agonist, displays robust antihyperglycemic and hypolipidemic activities. Biochemical and Biophysical Research Communications. 318(2). 323–328. 26 indexed citations
4.
Koyama, Hiroo, Daniel J. Miller, Ranjit C. Desai, et al.. (2004). (2R)-2-Ethylchromane-2-carboxylic Acids:  Discovery of Novel PPARα/γ Dual Agonists as Antihyperglycemic and Hypolipidemic Agents. Journal of Medicinal Chemistry. 47(12). 3255–3263. 50 indexed citations
5.
Guo, Qiu, Pei-Ran Wang, Denise P. Milot, et al.. (2001). Regulation of lipid metabolism and gene expression by fenofibrate in hamsters. Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids. 1533(3). 220–232. 53 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.
Hermanowski‐Vosatka, Anne, David Gerhold, Steven S. Mundt, et al.. (2000). PPARα Agonists Reduce 11β-Hydroxysteroid Dehydrogenase Type 1 in the Liver. Biochemical and Biophysical Research Communications. 279(2). 330–336. 85 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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