Jeffrey R. Schelling

8.2k total citations
84 papers, 3.2k citations indexed

About

Jeffrey R. Schelling is a scholar working on Nephrology, Molecular Biology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Jeffrey R. Schelling has authored 84 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Nephrology, 33 papers in Molecular Biology and 14 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Jeffrey R. Schelling's work include Chronic Kidney Disease and Diabetes (28 papers), Renal Diseases and Glomerulopathies (22 papers) and Dialysis and Renal Disease Management (11 papers). Jeffrey R. Schelling is often cited by papers focused on Chronic Kidney Disease and Diabetes (28 papers), Renal Diseases and Glomerulopathies (22 papers) and Dialysis and Renal Disease Management (11 papers). Jeffrey R. Schelling collaborates with scholars based in United States, Russia and Japan. Jeffrey R. Schelling's co-authors include John R. Sedor, Shenaz Khan, Stuart L. Linas, Martha Konieczkowski, Ronald P. Cleveland, Bassam G. Abu Jawdeh, Sudha K. Iyengar, Binghe Wang, Michael E. Ullian and Sujata Lakhe-Reddy and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Investigation and Annals of Internal Medicine.

In The Last Decade

Jeffrey R. Schelling

80 papers receiving 3.2k citations

Peers

Jeffrey R. Schelling
Jeffrey R. Schelling
Citations per year, relative to Jeffrey R. Schelling Jeffrey R. Schelling (= 1×) peers Toshiro Sugimoto

Countries citing papers authored by Jeffrey R. Schelling

Since Specialization
Citations

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

Fields of papers citing papers by Jeffrey R. Schelling

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jeffrey R. Schelling

This figure shows the co-authorship network connecting the top 25 collaborators of Jeffrey R. Schelling. A scholar is included among the top collaborators of Jeffrey R. Schelling 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 R. Schelling. Jeffrey R. Schelling 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.
Khan, Shenaz, Robert J. Gaivin, Zhiyu Liu, et al.. (2025). Fatty acid transport protein 2 inhibition enhances glucose tolerance through α cell–mediated GLP-1 secretion. Journal of Clinical Investigation. 135(23). 1 indexed citations
2.
Greenberg, Jason H., Alison G. Abraham, Yunwen Xu, et al.. (2025). Biomarker Panels for Discriminating Risk of CKD Progression in Children. Journal of the American Society of Nephrology. 36(6). 1105–1115. 1 indexed citations
3.
Coca, Steven G., Heather Thiessen‐Philbrook, Joachim H. Ix, et al.. (2025). The distal nephron biomarkers associate with diabetic kidney disease progression. JCI Insight. 10(12). 1 indexed citations
4.
Schrauben, Sarah J., Xiaoming Zhang, Dawei Xie, et al.. (2025). Urine Biomarkers for Diabetic Kidney Disease Progression in Participants of the Chronic Renal Insufficiency Cohort Study. Clinical Journal of the American Society of Nephrology. 20(7). 958–967. 4 indexed citations
5.
Katz, Ronit, Casey M. Rebholz, Mark J. Sarnak, et al.. (2024). Urine Biomarkers of Kidney Tubule Health and Risk of Incident CKD in Persons Without Diabetes: The ARIC, MESA, and REGARDS Studies. Kidney Medicine. 6(6). 100834–100834. 3 indexed citations
6.
Kumar, Mukesh, Robert J. Gaivin, Shenaz Khan, et al.. (2023). Definition of fatty acid transport protein-2 (FATP2) structure facilitates identification of small molecule inhibitors for the treatment of diabetic complications. International Journal of Biological Macromolecules. 244. 125328–125328. 11 indexed citations
7.
Sarnak, Mark J., Ronit Katz, Joachim H. Ix, et al.. (2022). Plasma Biomarkers as Risk Factors for Incident CKD. Kidney International Reports. 7(7). 1493–1501. 12 indexed citations
8.
Greenberg, Jason H., Alison G. Abraham, Yunwen Xu, et al.. (2021). Urine Biomarkers of Kidney Tubule Health, Injury, and Inflammation are Associated with Progression of CKD in Children. Journal of the American Society of Nephrology. 32(10). 2664–2677. 29 indexed citations
9.
Greenberg, Jason H., Alison G. Abraham, Yunwen Xu, et al.. (2020). Plasma Biomarkers of Tubular Injury and Inflammation Are Associated with CKD Progression in Children. Journal of the American Society of Nephrology. 31(5). 1067–1077. 48 indexed citations
10.
Park, Meyeon, Chi‐yuan Hsu, Alan S. Go, et al.. (2017). Urine Kidney Injury Biomarkers and Risks of Cardiovascular Disease Events and All-Cause Death: The CRIC Study. Clinical Journal of the American Society of Nephrology. 12(5). 761–771. 53 indexed citations
11.
Schelling, Jeffrey R.. (2015). Tubular atrophy in the pathogenesis of chronic kidney disease progression. Pediatric Nephrology. 31(5). 693–706. 122 indexed citations
12.
Rahman, Mahboob, Wei Yang, Sanjeev Akkina, et al.. (2014). Relation of Serum Lipids and Lipoproteins with Progression of CKD. Clinical Journal of the American Society of Nephrology. 9(7). 1190–1198. 129 indexed citations
13.
Lŭ, Lan, John R. Sedor, Vikas Gulani, et al.. (2011). Use of Diffusion Tensor MRI to Identify Early Changes in Diabetic Nephropathy. American Journal of Nephrology. 34(5). 476–482. 89 indexed citations
14.
Khan, Saeed R., Karen Wu, John R. Sedor, Bassam G. Abu Jawdeh, & Jeffrey R. Schelling. (2006). The NHE1 Na+/H+ exchanger regulates cell survival by activating and targeting ezrin to specific plasma membrane domains.. PubMed. 52(8). 115–21. 13 indexed citations
15.
Jarad, George, Jeffrey S. Simske, John R. Sedor, & Jeffrey R. Schelling. (2003). Nucleic acid-based techniques for post-transcriptional regulation of molecular targets. Current Opinion in Nephrology & Hypertension. 12(4). 415–421. 7 indexed citations
16.
El‐Meanawy, Ashraf, et al.. (2003). DNA expression analysis: serial analysis of gene expression, microarrays and kidney disease. Current Opinion in Nephrology & Hypertension. 12(4). 407–414. 14 indexed citations
17.
Iyengar, Sudha K., Jeffrey R. Schelling, & John R. Sedor. (2002). Approaches to understanding susceptibility to nephropathy: From genetics to genomics. Kidney International. 61(1). S61–S67. 13 indexed citations
18.
Schelling, Jeffrey R., et al.. (2002). Generation of Kidney Transcriptomes Using Serial Analysis of Gene Expression. Nephron Experimental Nephrology. 10(2). 82–92. 9 indexed citations
19.
Konieczkowski, Martha, et al.. (1999). Interleukin-1 stimulates Jun N-terminal/stress-activated protein kinase by an arachidonate-dependent mechanism in mesangial cells. Kidney International. 55(5). 1740–1749. 19 indexed citations
20.
Schelling, Jeffrey R., et al.. (1992). Cytoskeleton-dependent endocytosis is required for apical type 1 angiotensin II receptor-mediated phospholipase C activation in cultured rat proximal tubule cells.. Journal of Clinical Investigation. 90(6). 2472–2480. 76 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026