Jeffrey C. Hanselman

2.9k total citations · 2 hit papers
38 papers, 2.2k citations indexed

About

Jeffrey C. Hanselman is a scholar working on Surgery, Molecular Biology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Jeffrey C. Hanselman has authored 38 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Surgery, 12 papers in Molecular Biology and 10 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Jeffrey C. Hanselman's work include Lipoproteins and Cardiovascular Health (23 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (8 papers) and Cancer, Lipids, and Metabolism (7 papers). Jeffrey C. Hanselman is often cited by papers focused on Lipoproteins and Cardiovascular Health (23 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (8 papers) and Cancer, Lipids, and Metabolism (7 papers). Jeffrey C. Hanselman collaborates with scholars based in United States, Canada and United Kingdom. Jeffrey C. Hanselman's co-authors include Roger S. Newton, Lawrence A. Leiter, Xin Zhao, Christie M. Ballantyne, Clay T. Cramer, Diane MacDougall, Stephen L. Pinkosky, С. И. Филиппов, Narendra D. Lalwani and G.B. John Mancini and has published in prestigious journals such as JAMA, Circulation and SHILAP Revista de lepidopterología.

In The Last Decade

Jeffrey C. Hanselman

36 papers receiving 2.1k citations

Hit Papers

Effect of Bempedoic Acid vs Placebo Added to Maximally To... 2018 2026 2020 2023 2019 2018 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jeffrey C. Hanselman United States 19 1.3k 704 607 410 295 38 2.2k
Amanda J. Hooper Australia 26 1.5k 1.2× 391 0.6× 740 1.2× 432 1.1× 636 2.2× 107 2.3k
Shirya Rashid Canada 20 1.3k 1.0× 546 0.8× 795 1.3× 353 0.9× 378 1.3× 28 2.5k
Roberta Baetta Italy 22 944 0.7× 621 0.9× 300 0.5× 358 0.9× 253 0.9× 39 2.1k
Margaret E. Brousseau United States 24 1.7k 1.3× 560 0.8× 1.0k 1.7× 549 1.3× 330 1.1× 49 2.4k
Lizbeth Hoos United States 22 2.8k 2.1× 1.3k 1.8× 787 1.3× 661 1.6× 253 0.9× 30 4.0k
Maria Pia Adorni Italy 27 1.4k 1.1× 573 0.8× 678 1.1× 449 1.1× 440 1.5× 76 2.4k
Junji Koizumi Japan 27 2.5k 1.9× 903 1.3× 1.4k 2.3× 808 2.0× 684 2.3× 83 3.7k
Yassine Zaïr France 20 762 0.6× 445 0.6× 487 0.8× 202 0.5× 172 0.6× 34 1.5k
Howard G. Hutchinson United States 19 951 0.7× 729 1.0× 745 1.2× 256 0.6× 1.0k 3.5× 31 2.4k
Stephen L. Pinkosky United States 15 617 0.5× 754 1.1× 434 0.7× 343 0.8× 135 0.5× 19 1.6k

Countries citing papers authored by Jeffrey C. Hanselman

Since Specialization
Citations

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

Fields of papers citing papers by Jeffrey C. Hanselman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jeffrey C. Hanselman

This figure shows the co-authorship network connecting the top 25 collaborators of Jeffrey C. Hanselman. A scholar is included among the top collaborators of Jeffrey C. Hanselman 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 Jeffrey C. Hanselman. Jeffrey C. Hanselman 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.
Goldberg, Anne C., Maciej Banach, Alberico L. Catapano, et al.. (2023). Evaluation of the efficacy and safety of bempedoic acid in women and men: Pooled analyses from phase 3 trials. Atherosclerosis. 384. 117192–117192. 5 indexed citations
2.
Leiter, Lawrence A., Maciej Banach, Alberico L. Catapano, et al.. (2022). Bempedoic acid in patients with type 2 diabetes mellitus, prediabetes, and normoglycaemia: A post hoc analysis of efficacy and glycaemic control using pooled data from phase 3 clinical trials. Diabetes Obesity and Metabolism. 24(5). 868–880. 41 indexed citations
3.
Bays, Harold, Seth J. Baum, Eliot A. Brinton, et al.. (2021). Effect of bempedoic acid plus ezetimibe fixed-dose combination vs ezetimibe or placebo on low-density lipoprotein cholesterol in patients with type 2 diabetes and hypercholesterolemia not treated with statins. SHILAP Revista de lepidopterología. 8. 100278–100278. 12 indexed citations
4.
Rubino, John, Diane MacDougall, Lulu Ren Sterling, Jeffrey C. Hanselman, & Stephen J. Nicholls. (2020). Combination of bempedoic acid, ezetimibe, and atorvastatin in patients with hypercholesterolemia: A randomized clinical trial. Atherosclerosis. 320. 122–128. 60 indexed citations
5.
Leiter, Lawrence A., Maciej Banach, Alberico L. Catapano, et al.. (2019). Abstract 11417: Bempedoic Acid and Glycemic Control: A Pooled Analysis of 4 Phase 3 Clinical Trials. Circulation. 2 indexed citations
6.
Lalwani, Narendra D., Jeffrey C. Hanselman, Diane MacDougall, Lulu Ren Sterling, & Clay T. Cramer. (2019). Complementary low-density lipoprotein-cholesterol lowering and pharmacokinetics of adding bempedoic acid (ETC-1002) to high-dose atorvastatin background therapy in hypercholesterolemic patients: A randomized placebo-controlled trial. Journal of clinical lipidology. 13(4). 568–579. 55 indexed citations
7.
Ballantyne, Christie M., Maciej Banach, G.B. John Mancini, et al.. (2018). Efficacy and safety of bempedoic acid added to ezetimibe in statin-intolerant patients with hypercholesterolemia: A randomized, placebo-controlled study. Atherosclerosis. 277. 195–203. 294 indexed citations breakdown →
8.
Ballantyne, Christie M., James M. McKenney, Diane MacDougall, et al.. (2016). Effect of ETC-1002 on Serum Low-Density Lipoprotein Cholesterol in Hypercholesterolemic Patients Receiving Statin Therapy. The American Journal of Cardiology. 117(12). 1928–1933. 94 indexed citations
9.
Thompson, Paul D., Diane MacDougall, Roger S. Newton, et al.. (2016). Treatment with ETC-1002 alone and in combination with ezetimibe lowers LDL cholesterol in hypercholesterolemic patients with or without statin intolerance. Journal of clinical lipidology. 10(3). 556–567. 118 indexed citations
10.
Thompson, Paul D., Christie M. Ballantyne, James McKenney, et al.. (2015). ETC-1002 LOWERS LDL-C MORE THAN EZETIMIBE IN PATIENTS WITH HYPERCHOLESTEROLEMIA WITH OR WITHOUT STATIN INTOLERANCE AND HAS A SIMILAR SAFETY AND TOLERABILITY PROFILE. Journal of the American College of Cardiology. 65(10). A1349–A1349. 5 indexed citations
11.
Gutiérrez, María J., Diane MacDougall, Jeffrey C. Hanselman, et al.. (2014). Efficacy and Safety of ETC-1002, a Novel Investigational Low-Density Lipoprotein-Cholesterol–Lowering Therapy for the Treatment of Patients With Hypercholesterolemia and Type 2 Diabetes Mellitus. Arteriosclerosis Thrombosis and Vascular Biology. 34(3). 676–683. 135 indexed citations
12.
Srivastava, Rai Ajit K., Stephen L. Pinkosky, С. И. Филиппов, et al.. (2012). AMP-activated protein kinase: an emerging drug target to regulate imbalances in lipid and carbohydrate metabolism to treat cardio-metabolic diseases. Journal of Lipid Research. 53(12). 2490–2514. 240 indexed citations
13.
Pinkosky, Stephen L., С. И. Филиппов, Rahul Srivastava, et al.. (2012). AMP-activated protein kinase and ATP-citrate lyase are two distinct molecular targets for ETC-1002, a novel small molecule regulator of lipid and carbohydrate metabolism. Journal of Lipid Research. 54(1). 134–151. 191 indexed citations
14.
Homan, Reynold, Jeffrey C. Hanselman, Patrick A. Lester, et al.. (2010). Atherosclerosis in Octodon degus (degu) as a model for human disease. Atherosclerosis. 212(1). 48–54. 19 indexed citations
15.
Park, William K.C., Robert M. Kennedy, Scott D. Larsen, et al.. (2007). Hepatoselectivity of statins: Design and synthesis of 4-sulfamoyl pyrroles as HMG-CoA reductase inhibitors. Bioorganic & Medicinal Chemistry Letters. 18(3). 1151–1156. 45 indexed citations
16.
Auerbach, Bruce J., Chulho Choi, Jeffrey C. Hanselman, et al.. (2007). Discovery of pyrrole-based hepatoselective ligands as potent inhibitors of HMG-CoA reductase. Bioorganic & Medicinal Chemistry. 15(16). 5576–5589. 25 indexed citations
17.
Pfefferkorn, Jeffrey A., Chulho Choi, Yuntao Song, et al.. (2007). Design and synthesis of novel, conformationally restricted HMG-CoA reductase inhibitors. Bioorganic & Medicinal Chemistry Letters. 17(16). 4531–4537. 30 indexed citations
18.
Park, Tae‐Sik, Robert L. Panek, Mark D. Rekhter, et al.. (2006). Modulation of lipoprotein metabolism by inhibition of sphingomyelin synthesis in ApoE knockout mice. Atherosclerosis. 189(2). 264–272. 85 indexed citations
19.
Hanselman, Jeffrey C., et al.. (2001). Expression of the mRNA encoding truncated PPARα does not correlate with hepatic insensitivity to peroxisome proliferators. Molecular and Cellular Biochemistry. 217(1-2). 91–97. 19 indexed citations
20.
Rea, Thomas J., et al.. (2000). Elevated hepatic apolipoprotein A-I transcription is associated with diet-induced hyperalphalipoproteinemia in rabbits. Life Sciences. 66(18). 1683–1694. 6 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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