David J. Christini

3.8k total citations
101 papers, 2.8k citations indexed

About

David J. Christini is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, David J. Christini has authored 101 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 80 papers in Cardiology and Cardiovascular Medicine, 55 papers in Molecular Biology and 28 papers in Cellular and Molecular Neuroscience. Recurrent topics in David J. Christini's work include Cardiac electrophysiology and arrhythmias (74 papers), Ion channel regulation and function (48 papers) and Neuroscience and Neural Engineering (25 papers). David J. Christini is often cited by papers focused on Cardiac electrophysiology and arrhythmias (74 papers), Ion channel regulation and function (48 papers) and Neuroscience and Neural Engineering (25 papers). David J. Christini collaborates with scholars based in United States, United Kingdom and Netherlands. David J. Christini's co-authors include Trine Krogh‐Madsen, James J. Collins, Peter Jordan, Geoffrey W. Abbott, John A. White, Alan D. Dorval, Eric A. Sobie, Leon Glass, Kenneth M. Steín and Bruce B. Lerman and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Circulation.

In The Last Decade

David J. Christini

99 papers receiving 2.8k citations

Peers

David J. Christini
Elizabeth M. Cherry United States
Jorge M. Davidenko United States
L.J. Leon Canada
Alfonso Bueno‐Orovio United Kingdom
George W. Beeler United States
Elizabeth M. Cherry United States
David J. Christini
Citations per year, relative to David J. Christini David J. Christini (= 1×) peers Elizabeth M. Cherry

Countries citing papers authored by David J. Christini

Since Specialization
Citations

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

Fields of papers citing papers by David J. Christini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David J. Christini. 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 David J. Christini. The network helps show where David J. Christini may publish in the future.

Co-authorship network of co-authors of David J. Christini

This figure shows the co-authorship network connecting the top 25 collaborators of David J. Christini. A scholar is included among the top collaborators of David J. Christini 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 David J. Christini. David J. Christini 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.
Lei, Chon Lok, Michael Clerx, Teun P. de Boer, et al.. (2025). Resolving Artifacts in Voltage‐Clamp Experiments with Computational Modeling: An Application to Fast Sodium Current Recordings. Advanced Science. 12(30). e00691–e00691. 1 indexed citations
2.
Krogh‐Madsen, Trine, et al.. (2023). Optimization of a cardiomyocyte model illuminates role of increased INa,L in repolarization reserve. American Journal of Physiology-Heart and Circulatory Physiology. 326(2). H334–H345. 2 indexed citations
3.
Whittaker, David J., Michael Clerx, Chon Lok Lei, David J. Christini, & Gary R. Mirams. (2020). Calibration of ionic and cellular cardiac electrophysiology models. WIREs Systems Biology and Medicine. 12(4). e1482–e1482. 69 indexed citations
4.
Gaur, Namit, Arie O. Verkerk, Isabella Mengarelli, et al.. (2020). Validation of quantitative measure of repolarization reserve as a novel marker of drug induced proarrhythmia. Journal of Molecular and Cellular Cardiology. 145. 122–132. 11 indexed citations
5.
Krogh‐Madsen, Trine, et al.. (2018). Light-Activated Dynamic Clamp Using iPSC-Derived Cardiomyocytes. Biophysical Journal. 115(11). 2206–2217. 24 indexed citations
6.
Krogh‐Madsen, Trine, et al.. (2016). Population-Based Mathematical Modeling Facilitates the Interpretation of Dynamic Clamp Experiments in Cardiomyocytes. Biophysical Journal. 110(3). 585a–585a. 1 indexed citations
7.
Christini, David J., et al.. (2014). Dependence of phase-2 reentry and repolarization dispersion on epicardial and transmural ionic heterogeneity: a simulation study. EP Europace. 16(3). 458–465. 18 indexed citations
8.
Groenendaal, Willemijn, et al.. (2014). Voltage and Calcium Dynamics Both Underlie Cellular Alternans in Cardiac Myocytes. Biophysical Journal. 106(10). 2222–2232. 21 indexed citations
9.
Christini, David J., et al.. (2012). The Relative Influences of Phosphometabolites and pH on Action Potential Morphology during Myocardial Reperfusion: A Simulation Study. PLoS ONE. 7(11). e47117–e47117. 5 indexed citations
10.
Heerdt, Paul M., Zhaoyang Hu, Vikram A. Kanda, et al.. (2012). Transcriptomic analysis reveals atrial KCNE1 down‐regulation following lung lobectomy. Journal of Molecular and Cellular Cardiology. 53(3). 350–353. 11 indexed citations
11.
Christini, David J., et al.. (2011). NHE Inhibition Does Not Improve Na+ or Ca2+ Overload During Reperfusion: Using Modeling to Illuminate the Mechanisms Underlying a Therapeutic Failure. PLoS Computational Biology. 7(10). e1002241–e1002241. 20 indexed citations
12.
Gaeta, Stephen A., Trine Krogh‐Madsen, & David J. Christini. (2010). Feedback-control induced pattern formation in cardiac myocytes: A mathematical modeling study. Journal of Theoretical Biology. 266(3). 408–418. 22 indexed citations
13.
Xu, Xianghua, Vikram A. Kanda, Eun Joo Choi, et al.. (2009). MinK-dependent internalization of the IKs potassium channel. Cardiovascular Research. 82(3). 430–438. 36 indexed citations
14.
Ahrens‐Nicklas, Rebecca C. & David J. Christini. (2009). Anthropomorphizing the Mouse Cardiac Action Potential via a Novel Dynamic Clamp Method. Biophysical Journal. 97(10). 2684–2692. 16 indexed citations
15.
Gordon, Earl, Gianina Panaghie, Liyong Deng, et al.. (2007). A KCNE2 mutation in a patient with cardiac arrhythmia induced by auditory stimuli and serum electrolyte imbalance. Cardiovascular Research. 77(1). 98–106. 28 indexed citations
16.
Krogh‐Madsen, Trine & David J. Christini. (2006). Action Potential Duration Dispersion and Alternans in Simulated Heterogeneous Cardiac Tissue with a Structural Barrier. Biophysical Journal. 92(4). 1138–1149. 24 indexed citations
17.
Jordan, Peter & David J. Christini. (2005). Action Potential Morphology Influences Intracellular Calcium Handling Stability and the Occurrence of Alternans. Biophysical Journal. 90(2). 672–680. 31 indexed citations
18.
Jordan, Peter & David J. Christini. (2004). Adaptive Diastolic Interval Control of Cardiac Action Potential Duration Alternans. Journal of Cardiovascular Electrophysiology. 15(10). 1177–1185. 27 indexed citations
19.
Tang, Lilong, David J. Christini, & Jay M. Edelberg. (2003). Genetically Engineered Biologically Based Hemostatic Bioassay. Annals of Biomedical Engineering. 31(2). 159–162. 3 indexed citations
20.
Sinha, Sitabhra & David J. Christini. (2002). Termination of reentry in an inhomogeneous ring of model cardiac cells. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 66(6). 61903–61903. 18 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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