Andrew M. Glazer

2.7k total citations
38 papers, 1.3k citations indexed

About

Andrew M. Glazer is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine and Genetics. According to data from OpenAlex, Andrew M. Glazer has authored 38 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 23 papers in Cardiology and Cardiovascular Medicine and 16 papers in Genetics. Recurrent topics in Andrew M. Glazer's work include Cardiac electrophysiology and arrhythmias (21 papers), Ion channel regulation and function (12 papers) and Genomics and Rare Diseases (7 papers). Andrew M. Glazer is often cited by papers focused on Cardiac electrophysiology and arrhythmias (21 papers), Ion channel regulation and function (12 papers) and Genomics and Rare Diseases (7 papers). Andrew M. Glazer collaborates with scholars based in United States, Australia and Canada. Andrew M. Glazer's co-authors include Dan M. Roden, Craig T. Miller, Brett M. Kroncke, Emily Killingbeck, Phillip A. Cleves, Therese Mitros, Daniel S. Rokhsar, Quinn S. Wells, Matthew J. O’Neill and Björn C. Knollmann and has published in prestigious journals such as Circulation, Nature Communications and Journal of the American College of Cardiology.

In The Last Decade

Andrew M. Glazer

34 papers receiving 1.3k citations

Peers

Andrew M. Glazer

CCM

GENET

PRM

IMMUN

Hironori Ueda Japan

Jeffrey C. Sellers United States

Katsuhiro FUKUTA Japan

Rie Ichikawa Japan

Gábor Mátyás Switzerland

Alex V. Postma Netherlands

Nicola Marziliano Italy

Jewell C. Ward United States

Cecilia Lanny Winata Poland

Andrea Tóth Hungary

Hironori Ueda Japan

Andrew M. Glazer

384 ×0.7

347 ×0.7

CCM

410 ×1.0

GENET

58 ×0.3

PRM

197 ×2.5

IMMUN

Citations per year, relative to Andrew M. Glazer Andrew M. Glazer (= 1×) peers Hironori Ueda

Countries citing papers authored by Andrew M. Glazer

Since Specialization

Citations

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

Fields of papers citing papers by Andrew M. Glazer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew M. Glazer. 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 Andrew M. Glazer. The network helps show where Andrew M. Glazer may publish in the future.

Co-authorship network of co-authors of Andrew M. Glazer

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew M. Glazer. A scholar is included among the top collaborators of Andrew M. Glazer 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 Andrew M. Glazer. Andrew M. Glazer 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

O’Neill, Matthew J., Joseph F. Solus, G Harvey, et al.. (2025). Automated patch clamp data improve variant classification and penetrance stratification for SCN5A –Brugada syndrome. European Heart Journal.

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.

O’Neill, Matthew J., Tao Yang, Julie Laudeman, et al.. (2024). ParSE-seq: a calibrated multiplexed assay to facilitate the clinical classification of putative splice-altering variants. Nature Communications. 15(1). 8320–8320. 3 indexed citations

Claussnitzer, Melina, Victoria N. Parikh, Alex H. Wagner, et al.. (2024). Minimum information and guidelines for reporting a multiplexed assay of variant effect. Genome biology. 25(1). 100–100. 8 indexed citations

O’Neill, Matthew J., Ebony Richardson, Kate Thomson, et al.. (2024). Multisite Validation of a Functional Assay to Adjudicate SCN5A Brugada Syndrome–Associated Variants. Circulation Genomic and Precision Medicine. 17(4). e004569–e004569. 3 indexed citations

O’Neill, Matthew J., Ebony Richardson, Kate Thomson, et al.. (2023). Utility of a High-Throughput Electrophysiology Assay to Determine Pathogenicity of SCN5A Variants Associated With Brugada Syndrome. Heart Lung and Circulation. 32. S131–S132. 1 indexed citations

Gulsevin, Alican, Andrew M. Glazer, Tiffany Shields, et al.. (2022). Veratridine Can Bind to a Site at the Mouth of the Channel Pore at Human Cardiac Sodium Channel NaV1.5. International Journal of Molecular Sciences. 23(4). 2225–2225. 4 indexed citations

Glazer, Andrew M.. (2022). Genetics of congenital arrhythmia syndromes: the challenge of variant interpretation. Current Opinion in Genetics & Development. 77. 102004–102004. 6 indexed citations

O’Neill, Matthew J., Li Bian, Yuko Wada, et al.. (2022). Dominant negative effects of SCN5A missense variants. Genetics in Medicine. 24(6). 1238–1248. 16 indexed citations

10.

Kroncke, Brett M., Derek K. Smith, Yi Zuo, et al.. (2020). A Bayesian method to estimate variant-induced disease penetrance. PLoS Genetics. 16(6). e1008862–e1008862. 13 indexed citations

11.

Kozek, Krystian A., Andrew M. Glazer, Chai‐Ann Ng, et al.. (2020). High-throughput discovery of trafficking-deficient variants in the cardiac potassium channel KV11.1. Heart Rhythm. 17(12). 2180–2189. 32 indexed citations

12.

Glazer, Andrew M., Yuko Wada, Bian Li, et al.. (2020). High-Throughput Reclassification of SCN5A Variants. The American Journal of Human Genetics. 107(1). 111–123. 83 indexed citations

13.

Kryshtal, Dmytro O., Shan Parikh, Lili Wang, et al.. (2019). Patient-independent human induced pluripotent stem cell model: A new tool for rapid determination of genetic variant pathogenicity in long QT syndrome. Heart Rhythm. 16(11). 1686–1695. 37 indexed citations

14.

Johnson, Christopher N., F Potet, Brett M. Kroncke, et al.. (2018). A Mechanism of Calmodulin Modulation of the Human Cardiac Sodium Channel. Structure. 26(5). 683–694.e3. 41 indexed citations

15.

Grouthier, Virginie, Bénédicte Lebrun‐Vignes, Andrew M. Glazer, et al.. (2018). Increased long QT and torsade de pointes reporting on tamoxifen compared with aromatase inhibitors. Heart. 104(22). 1859–1863. 40 indexed citations

16.

Karnes, Jason H., Lisa Bastarache, Christian M. Shaffer, et al.. (2017). Phenome-wide scanning identifies multiple diseases and disease severity phenotypes associated with HLA variants. Science Translational Medicine. 9(389). 74 indexed citations

17.

Karnes, Jason H., Christian M. Shaffer, Lisa Bastarache, et al.. (2017). Comparison of HLA allelic imputation programs. PLoS ONE. 12(2). e0172444–e0172444. 44 indexed citations

18.

Assad, Tufik R., Anna R. Hemnes, Emma K. Larkin, et al.. (2016). Clinical and Biological Insights Into Combined Post- and Pre-Capillary Pulmonary Hypertension. Journal of the American College of Cardiology. 68(23). 2525–2536. 142 indexed citations

19.

Glazer, Andrew M., et al.. (2014). Parallel developmental genetic features underlie stickleback gill raker evolution. EvoDevo. 5(1). 19–19. 35 indexed citations

20.

Glazer, Andrew M., Alex W. Wilkinson, Chelsea B. Backer, et al.. (2009). The Zn Finger protein Iguana impacts Hedgehog signaling by promoting ciliogenesis. Developmental Biology. 337(1). 148–156. 80 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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