Megan Lancaster

439 total citations
10 papers, 210 citations indexed

About

Megan Lancaster is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology and Genetics. According to data from OpenAlex, Megan Lancaster has authored 10 papers receiving a total of 210 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Cardiology and Cardiovascular Medicine, 2 papers in Molecular Biology and 2 papers in Genetics. Recurrent topics in Megan Lancaster's work include Cardiovascular Function and Risk Factors (3 papers), Genomics and Rare Diseases (2 papers) and Cardiac Arrhythmias and Treatments (2 papers). Megan Lancaster is often cited by papers focused on Cardiovascular Function and Risk Factors (3 papers), Genomics and Rare Diseases (2 papers) and Cardiac Arrhythmias and Treatments (2 papers). Megan Lancaster collaborates with scholars based in United States, Canada and Taiwan. Megan Lancaster's co-authors include Partho P. Sengupta, Jagat Narula, Alaa Mabrouk Salem Omar, Sukrit Narula, Hemant Kulkarni, Dan M. Roden, Rebecca R. Hung, D. Marshall Brinkley, Sean G. Hughes and William G. Stevenson and has published in prestigious journals such as Nature Communications, Journal of the American College of Cardiology and Circulation Research.

In The Last Decade

Megan Lancaster

7 papers receiving 209 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Megan Lancaster United States 4 157 66 44 21 17 10 210
Jun Hyuk Kang South Korea 10 126 0.8× 90 1.4× 40 0.9× 6 0.3× 7 0.4× 25 282
Marc Landsman United States 9 32 0.2× 69 1.0× 50 1.1× 16 0.8× 31 1.8× 20 261
Zhuoran Xu United States 8 63 0.4× 34 0.5× 45 1.0× 4 0.2× 21 1.2× 13 210
Chuanyan Wu China 8 133 0.8× 176 2.7× 50 1.1× 39 1.9× 18 344
Gavin S. Chu United Kingdom 12 248 1.6× 39 0.6× 16 0.4× 6 0.3× 49 355
Angelika Szengel Germany 6 20 0.1× 80 1.2× 12 0.3× 69 3.3× 6 0.4× 7 211
Slawomir Weretka Germany 12 357 2.3× 74 1.1× 19 0.4× 7 0.3× 22 399
Danila Vella Italy 6 70 0.4× 110 1.7× 17 0.4× 37 1.8× 15 255
Yizhi Pan China 6 44 0.3× 28 0.4× 30 0.7× 4 0.2× 5 0.3× 12 220
Amirhossein Kiani United States 3 10 0.1× 65 1.0× 63 1.4× 6 0.3× 28 1.6× 4 204

Countries citing papers authored by Megan Lancaster

Since Specialization
Citations

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

Fields of papers citing papers by Megan Lancaster

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Megan Lancaster

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

All Works

10 of 10 papers shown
1.
Glazer, Andrew M., Victoria N. Parikh, Brett M. Kroncke, et al.. (2025). Creating an atlas of variant effects to resolve variants of uncertain significance and guide cardiovascular medicine. Nature Reviews Cardiology. 23(3). 149–163.
2.
Kuang, Da, Megan Lancaster, Roujia Li, et al.. (2024). Benchmarking computational variant effect predictors by their ability to infer human traits. Genome biology. 25(1). 172–172. 12 indexed citations
3.
Lancaster, Megan, Hung‐Hsin Chen, M. Benjamin Shoemaker, et al.. (2024). Detection of distant relatedness in biobanks to identify undiagnosed cases of Mendelian disease as applied to Long QT syndrome. Nature Communications. 15(1). 7507–7507.
4.
Lancaster, Megan, et al.. (2022). Left atrial appendage dimension predicts elevated brain natriuretic peptide in nonvalvular atrial fibrillation. Journal of Cardiovascular Electrophysiology. 34(1). 135–141. 1 indexed citations
5.
Lancaster, Megan, William G. Stevenson, Rebecca R. Hung, et al.. (2022). Arrhythmias as Presentation of Genetic Cardiomyopathy. Circulation Research. 130(11). 1698–1722. 34 indexed citations
6.
Lancaster, Megan, et al.. (2021). A challenging VT ablation with a large cardiac tumor. Journal of Cardiovascular Electrophysiology. 32(9). 2604–2606.
7.
Lancaster, Megan, Alaa Mabrouk Salem Omar, Sukrit Narula, et al.. (2018). Phenotypic Clustering of Left Ventricular Diastolic Function Parameters. JACC. Cardiovascular imaging. 12(7). 1149–1161. 67 indexed citations
8.
Omar, Alaa Mabrouk Salem, et al.. (2018). COMPUTATIONAL UNSUPERVISED CLUSTERING OF ECHOCARDIOGRAPHIC VARIABLES FOR THE ASSESSMENT OF DIASTOLIC DYSFUNCTION SEVERITY. Journal of the American College of Cardiology. 71(11). A1519–A1519. 2 indexed citations
9.
Lancaster, Megan, et al.. (2016). Improved Prediction of Drug‐Induced Torsades de Pointes Through Simulations of Dynamics and Machine Learning Algorithms. Clinical Pharmacology & Therapeutics. 100(4). 371–379. 93 indexed citations
10.
Wong, David H., et al.. (1999). THE EFFECT OF OXYGEN ON PULMONARY MUSCLE FUNCTION IN PATIENTS WITH SPINAL CORD INJURY. Anesthesia & Analgesia. 88(2S). 421S–421S. 1 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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Rankless by CCL
2026