Ivan Gerling

5.2k total citations · 1 hit paper
111 papers, 3.8k citations indexed

About

Ivan Gerling is a scholar working on Genetics, Endocrinology, Diabetes and Metabolism and Surgery. According to data from OpenAlex, Ivan Gerling has authored 111 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Genetics, 43 papers in Endocrinology, Diabetes and Metabolism and 39 papers in Surgery. Recurrent topics in Ivan Gerling's work include Diabetes and associated disorders (43 papers), Pancreatic function and diabetes (29 papers) and Hormonal Regulation and Hypertension (22 papers). Ivan Gerling is often cited by papers focused on Diabetes and associated disorders (43 papers), Pancreatic function and diabetes (29 papers) and Hormonal Regulation and Hypertension (22 papers). Ivan Gerling collaborates with scholars based in United States, Australia and Bangladesh. Ivan Gerling's co-authors include Karl T. Weber, Yao Sun, Robert A. Ahokas, Syamal K. Bhattacharya, Edward H. Leiter, Nataliya Lenchik, David Serreze, Nando K. Chatterjee, Vaibhav Mundra and Ram I. Mahato and has published in prestigious journals such as Journal of Biological Chemistry, Circulation and The Journal of Immunology.

In The Last Decade

Ivan Gerling

110 papers receiving 3.8k citations

Hit Papers

align trajectories

What are hit papers?

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.

Myofibroblast-mediated mechanisms of pathological remodelling of the heart

2012 503 citations Karl T. Weber, Yao Sun et al. Nature Reviews Cardiology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ivan Gerling United States	34	1.2k	1.1k	1.1k	995	958	111	3.8k
Miki Nagase Japan	33	732 0.6×	1.4k 1.2×	1.4k 1.4×	351 0.4×	686 0.7×	82	3.9k
Tomomi Fujisawa Japan	33	867 0.7×	1.0k 0.9×	986 0.9×	1.1k 1.1×	353 0.4×	169	3.9k
Adam E. Mullick United States	32	1.0k 0.8×	1.5k 1.3×	885 0.8×	291 0.3×	966 1.0×	79	4.0k
Hiroshi Kawachi Japan	46	694 0.6×	2.7k 2.4×	682 0.6×	768 0.8×	693 0.7×	174	6.5k
Liliane J. Striker United States	48	828 0.7×	2.2k 1.9×	1.8k 1.7×	933 0.9×	622 0.6×	115	6.9k
Roger F.L. James United Kingdom	33	2.2k 1.7×	1.5k 1.3×	1.2k 1.1×	1.2k 1.2×	315 0.3×	110	4.1k
Norman C.W. Wong Canada	42	1.3k 1.0×	2.9k 2.5×	1.4k 1.3×	1.1k 1.1×	424 0.4×	144	5.5k
Francesco Paolo Mancini Italy	32	803 0.6×	1.5k 1.3×	404 0.4×	305 0.3×	554 0.6×	86	3.9k
Mary G. Sorci‐Thomas United States	38	1.8k 1.5×	1.8k 1.6×	1.2k 1.1×	231 0.2×	462 0.5×	85	4.4k
Vanesa Esteban Spain	30	458 0.4×	1.6k 1.4×	741 0.7×	263 0.3×	1.5k 1.6×	72	4.2k

Countries citing papers authored by Ivan Gerling

Since Specialization

Citations

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

Fields of papers citing papers by Ivan Gerling

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ivan Gerling

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

All Works

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20 of 20 papers shown

Butterworth, Elizabeth A., Nataliya Lenchik, Jing Chen, et al.. (2025). Beta cell dysfunction occurs independently of insulitis in type 1 diabetes pathogenesis. Cell Reports. 44(9). 116174–116174. 1 indexed citations

Buschard, Karsten, Lars Krogvold, Flemming Pociot, et al.. (2025). TLR5 influences the development of type 1 diabetes. BMJ Open Diabetes Research & Care. 13(5). e005111–e005111.

Buschard, Karsten, et al.. (2023). Type 1 diabetes could begin with alterations in innate anti‐viral immunity, which are already at this stage associated with HLA risk haplotypes. Diabetes/Metabolism Research and Reviews. 39(7). e3678–e3678. 1 indexed citations

Leung, Sherman S., Nataliya Lenchik, Clayton E. Mathews, et al.. (2023). Alpha cell receptor for advanced glycation end products associate with glucagon expression in type 1 diabetes. Scientific Reports. 13(1). 12948–12948. 4 indexed citations

Krogvold, Lars, Pia Leete, Mark A. Russell, et al.. (2022). Detection of Antiviral Tissue Responses and Increased Cell Stress in the Pancreatic Islets of Newly Diagnosed Type 1 Diabetes Patients: Results From the DiViD Study. Frontiers in Endocrinology. 13. 881997–881997. 11 indexed citations

Apaolaza, Paola S., Jose Zapardiel‐Gonzalo, Grace Nelson, et al.. (2021). Islet expression of type I interferon response sensors is associated with immune infiltration and viral infection in type 1 diabetes. Science Advances. 7(9). 50 indexed citations

Haupt‐Jorgensen, Martin, Lars Krogvold, Simranjeet Kaur, et al.. (2021). Genetic predisposition in the 2′-5′A pathway in the development of type 1 diabetes: potential contribution to dysregulation of innate antiviral immunity. Diabetologia. 64(8). 1805–1815. 17 indexed citations

Hollingsworth, TJ, Francesco Giorgianni, Nataliya Lenchik, et al.. (2015). The Cu/Zn+ superoxide dismutase knockout mouse (Sod1-/-), a model of age-related macular degeneration (AMD), exhibits anti-retinal autoantibodies (AAbs) and marked signs of intraretinal inflammation prior to onset of an AMD-like phenotype. Investigative Ophthalmology & Visual Science. 56(7). 3986–3986. 1 indexed citations

Hollingsworth, TJ, Isabelle Meunier, Nataliya Lenchik, et al.. (2015). Defective mer-tyrosine kinase (mer-TK) function is associated with anti-arrestin and anti-interphotoreceptor retinoid-binding protein (IRBP) autoantibodies (AAbs) in Mer, Axl, Tyro3 -/-(TAM) mice and in autosomal recessive retinitis pigmentosa (arRP) patients with a null MERTK mutation. Investigative Ophthalmology & Visual Science. 56(7). 169–169. 3 indexed citations

10.

Gerling, Ivan, Robert A. Ahokas, Wenyuan Zhao, et al.. (2013). Gene Expression Profiles of Peripheral Blood Mononuclear Cells Reveal Transcriptional Signatures as Novel Biomarkers of Cardiac Remodeling in Rats With Aldosteronism and Hypertensive Heart Disease. JACC Heart Failure. 1(6). 469–476. 20 indexed citations

11.

Zhao, Wenyuan, Tieqiang Zhao, Robert A. Ahokas, et al.. (2013). Nebivolol. Journal of Cardiovascular Pharmacology. 62(5). 445–451. 19 indexed citations

12.

Shahbaz, Atta U., Robert A. Ahokas, Yao Sun, et al.. (2012). Mitochondria play a central role in nonischemic cardiomyocyte necrosis: common to acute and chronic stressor states. Pflügers Archiv - European Journal of Physiology. 464(1). 123–131. 27 indexed citations

13.

Weber, Karl T., Yao Sun, Syamal K. Bhattacharya, Robert A. Ahokas, & Ivan Gerling. (2012). Myofibroblast-mediated mechanisms of pathological remodelling of the heart. Nature Reviews Cardiology. 10(1). 15–26. 503 indexed citations breakdown →

14.

Zhao, Wenyuan, Tieqiang Zhao, Robert A. Ahokas, et al.. (2011). Mitochondriocentric Pathway to Cardiomyocyte Necrosis in Aldosteronism: Cardioprotective Responses to Carvedilol and Nebivolol. Journal of Cardiovascular Pharmacology. 58(1). 80–86. 22 indexed citations

15.

Zhao, Tieqiang, Wenyuan Zhao, Syamal K. Bhattacharya, et al.. (2008). Causes and Consequences of Zinc Dyshomeostasis in Rats With Chronic Aldosteronism. Journal of Cardiovascular Pharmacology. 52(3). 245–252. 46 indexed citations

16.

Majumdar, Gipsy, et al.. (2005). Insulin Dynamically Regulates Calmodulin Gene Expression by Sequential O-Glycosylation and Phosphorylation of Sp1 and Its Subcellular Compartmentalization in Liver Cells. Journal of Biological Chemistry. 281(6). 3642–3650. 79 indexed citations

17.

Tannu, Nilesh S., Vamshi K. Rao, Himanshu S. Gadgil, et al.. (2004). Paraffin-wax-coated plates as matrix-assisted laser desorption/ionization sample support for high-throughput identification of proteins by peptide mass fingerprinting. Analytical Biochemistry. 327(2). 222–232. 55 indexed citations

18.

Gadgil, Himanshu S., Francesco Giorgianni, Edward S. Umstot, et al.. (2003). Proteome of monocytes primed with lipopolysaccharide: Analysis of the abundant proteins. PROTEOMICS. 3(9). 1767–1780. 49 indexed citations

19.

Serreze, David, H.D. Chapman, Don S. Varnum, et al.. (1997). Initiation of autoimmune diabetes in NOD/Lt mice is MHC class I-dependent. The Journal of Immunology. 158(8). 3978–3986. 114 indexed citations

20.

Gerling, Ivan, et al.. (1994). The Thymus as a Site for Evaluating the Potency of Candidate β Cell Autoantigens in NOD Mice. Journal of Autoimmunity. 7(6). 851–858. 10 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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