Aaron D. Kaplan

1.9k total citations
17 papers, 837 citations indexed

About

Aaron D. Kaplan is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine and Cellular and Molecular Neuroscience. According to data from OpenAlex, Aaron D. Kaplan has authored 17 papers receiving a total of 837 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 10 papers in Cardiology and Cardiovascular Medicine and 5 papers in Cellular and Molecular Neuroscience. Recurrent topics in Aaron D. Kaplan's work include Cardiac electrophysiology and arrhythmias (7 papers), Pluripotent Stem Cells Research (5 papers) and Neuroscience and Neural Engineering (5 papers). Aaron D. Kaplan is often cited by papers focused on Cardiac electrophysiology and arrhythmias (7 papers), Pluripotent Stem Cells Research (5 papers) and Neuroscience and Neural Engineering (5 papers). Aaron D. Kaplan collaborates with scholars based in United States, United Kingdom and Canada. Aaron D. Kaplan's co-authors include Randall L. Rasmusson, Glenna C.L. Bett, Bo Lin, Lei Yang, Agnieszka Lis, Lu Han, Barry London, John P. Perdew, Mel Levy and Guy Salama and has published in prestigious journals such as Circulation Research, Development and The FASEB Journal.

In The Last Decade

Aaron D. Kaplan

17 papers receiving 832 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Aaron D. Kaplan United States 11 429 302 163 149 123 17 837
Julien Robert‐Paganin France 15 344 0.8× 379 1.3× 27 0.2× 21 0.1× 51 0.4× 20 656
Esa‐Pekka Kumpula Finland 11 220 0.5× 27 0.1× 32 0.2× 61 0.4× 67 0.5× 17 402
Patricia M. Fagnant United States 17 338 0.8× 379 1.3× 27 0.2× 27 0.2× 39 0.3× 24 591
Margaretha Lindroth Sweden 14 378 0.9× 70 0.2× 50 0.3× 11 0.1× 46 0.4× 20 713
Lynn R. Chrin United States 11 259 0.6× 131 0.4× 15 0.1× 27 0.2× 23 0.2× 34 463
Naoko Doi Japan 17 508 1.2× 122 0.4× 181 1.1× 13 0.1× 91 0.7× 30 813
Hiroshi Ohtsuka Japan 13 325 0.8× 161 0.5× 49 0.3× 6 0.0× 155 1.3× 57 718
John D. Harding United States 16 272 0.6× 548 1.8× 17 0.1× 4 0.0× 34 0.3× 35 1.1k
Paul A. Steimle United States 13 192 0.4× 54 0.2× 32 0.2× 118 0.8× 16 0.1× 18 496
Ubirajara Agero Brazil 14 176 0.4× 22 0.1× 19 0.1× 10 0.1× 34 0.3× 28 533

Countries citing papers authored by Aaron D. Kaplan

Since Specialization
Citations

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

Fields of papers citing papers by Aaron D. Kaplan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Aaron D. Kaplan. 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 Aaron D. Kaplan. The network helps show where Aaron D. Kaplan may publish in the future.

Co-authorship network of co-authors of Aaron D. Kaplan

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

All Works

17 of 17 papers shown
1.
Kaplan, Aaron D., Liron Boyman, Christopher W. Ward, W. Jonathan Lederer, & Maura Greiser. (2024). Ryanodine receptor stabilization therapy suppresses Ca2+- based arrhythmias in a novel model of metabolic HFpEF. Journal of Molecular and Cellular Cardiology. 195. 68–72. 3 indexed citations
2.
Greiser, Maura, Mariusz Karbowski, Aaron D. Kaplan, et al.. (2023). Calcium and bicarbonate signaling pathways have pivotal, resonating roles in matching ATP production to demand. eLife. 12. 7 indexed citations
3.
Kaplan, Aaron D., Mel Levy, & John P. Perdew. (2023). The Predictive Power of Exact Constraints and Appropriate Norms in Density Functional Theory. Annual Review of Physical Chemistry. 74(1). 193–218. 50 indexed citations
4.
Kaplan, Aaron D., Humberto C. Joca, Liron Boyman, & Maura Greiser. (2021). Calcium Signaling Silencing in Atrial Fibrillation: Implications for Atrial Sodium Homeostasis. International Journal of Molecular Sciences. 22(19). 10513–10513. 10 indexed citations
5.
Kaplan, Aaron D., et al.. (2020). ‘Calcium Clock’ at the Nanoscale in the RAT SA Node: 3D Ryanodine Receptor Cluster Organization and Intracellular Ca2+ Signaling. Biophysical Journal. 118(3). 173a–173a. 1 indexed citations
6.
Kaplan, Aaron D., Randall L. Rasmusson, & Glenna C.L. Bett. (2016). Ionic Basis of Repolarization of Atrial and Ventricular Specific Cell Types Derived from Human Induced Pluripotent Stem Cells. Biophysical Journal. 110(3). 343a–343a. 2 indexed citations
7.
Kim, Jong J., Lei Yang, Bo Lin, et al.. (2015). Mechanism of automaticity in cardiomyocytes derived from human induced pluripotent stem cells. Journal of Molecular and Cellular Cardiology. 81. 81–93. 84 indexed citations
8.
Cordeiro, Jonathan M., Robert J. Goodrow, Aaron D. Kaplan, et al.. (2015). Regional variation of the inwardly rectifying potassium current in the canine heart and the contributions to differences in action potential repolarization. Journal of Molecular and Cellular Cardiology. 84. 52–60. 23 indexed citations
9.
Gold, Daniel, Aaron D. Kaplan, Agnieszka Lis, et al.. (2015). The Toxoplasma Dense Granule Proteins GRA17 and GRA23 Mediate the Movement of Small Molecules between the Host and the Parasitophorous Vacuole. Cell Host & Microbe. 17(5). 642–652. 182 indexed citations
10.
Lin, Bo, Yang Li, Lu Han, et al.. (2015). Modeling and study of the mechanism of dilated cardiomyopathy using induced pluripotent stem cells derived from individuals with Duchenne muscular dystrophy. Disease Models & Mechanisms. 8(5). 457–466. 90 indexed citations
11.
12.
Kaplan, Aaron D., Agnieszka Lis, Thomas R. Cimato, et al.. (2014). Enhanced Differentiation of Stem Cell Derived Cardiac Myocytes by Electronic Expression of IK1 Reveals an Atrial-Specific Kv1.5-Like Current. Biophysical Journal. 106(2). 631a–631a. 1 indexed citations
13.
Han, Lu, Yang Li, Jason Tchao, et al.. (2014). Study familial hypertrophic cardiomyopathy using patient-specific induced pluripotent stem cells. Cardiovascular Research. 104(2). 258–269. 146 indexed citations
14.
Parikh, Ashish, Divyang Patel, Charles F. McTiernan, et al.. (2013). Relaxin Suppresses Atrial Fibrillation by Reversing Fibrosis and Myocyte Hypertrophy and Increasing Conduction Velocity and Sodium Current in Spontaneously Hypertensive Rat Hearts. Circulation Research. 113(3). 313–321. 93 indexed citations
15.
Bett, Glenna C.L., Aaron D. Kaplan, Agnieszka Lis, et al.. (2013). Electronic “expression” of the inward rectifier in cardiocytes derived from human-induced pluripotent stem cells. Heart Rhythm. 10(12). 1903–1910. 89 indexed citations
16.
Adler, Eric, Vincent C. Chen, Aaron D. Kaplan, et al.. (2009). The cardiomyocyte lineage is critical for optimization of stem cell therapy in a mouse model of myocardial infarction. The FASEB Journal. 24(4). 1073–1081. 13 indexed citations
17.
Kaplan, Aaron D., Ariel J. Jaffa, Ilan E. Timor‐Tritsch, & David Elad. (2009). Hemodynamic Analysis of Arterial Blood Flow in the Coiled Umbilical Cord. Reproductive Sciences. 17(3). 258–268. 40 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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