Ryan Sprissler

1.7k total citations · 1 hit paper
20 papers, 547 citations indexed

About

Ryan Sprissler is a scholar working on Cardiology and Cardiovascular Medicine, Genetics and Psychiatry and Mental health. According to data from OpenAlex, Ryan Sprissler has authored 20 papers receiving a total of 547 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Cardiology and Cardiovascular Medicine, 5 papers in Genetics and 5 papers in Psychiatry and Mental health. Recurrent topics in Ryan Sprissler's work include Blood Pressure and Hypertension Studies (6 papers), Epilepsy research and treatment (5 papers) and Hormonal Regulation and Hypertension (4 papers). Ryan Sprissler is often cited by papers focused on Blood Pressure and Hypertension Studies (6 papers), Epilepsy research and treatment (5 papers) and Hormonal Regulation and Hypertension (4 papers). Ryan Sprissler collaborates with scholars based in United States, Germany and United Kingdom. Ryan Sprissler's co-authors include Michael F. Hammer, Laurel Johnstone, Ian L. Pepper, Samendra P. Sherchan, Aidan R. Foster, David T. Harris, Bradley W. Schmitz, Sarah M. Prasek, Charles P. Gerba and Kristen M. Brown and has published in prestigious journals such as Nature Communications, PLoS ONE and The Science of The Total Environment.

In The Last Decade

Ryan Sprissler

17 papers receiving 536 citations

Hit Papers

COVID-19 containment on a college campus via wastewater-b... 2021 2026 2022 2024 2021 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ryan Sprissler United States 8 206 187 182 119 108 20 547
Siqi Hong China 14 85 0.4× 59 0.3× 199 1.1× 25 0.2× 127 1.2× 62 560
Micha Gawlik Germany 10 52 0.3× 78 0.4× 98 0.5× 25 0.2× 50 0.5× 14 326
Matthew B. Friese United States 11 92 0.4× 98 0.5× 284 1.6× 13 0.1× 12 0.1× 15 710
Sylvie Devalle Brazil 12 196 1.0× 92 0.5× 115 0.6× 27 0.2× 12 0.1× 25 556
Louise Hartley United Kingdom 7 41 0.2× 56 0.3× 299 1.6× 28 0.2× 29 0.3× 20 478
Tetyana P. Buzhdygan United States 9 220 1.1× 85 0.5× 277 1.5× 55 0.5× 3 0.0× 11 753
An Vanhaesebrouck United Kingdom 14 38 0.2× 75 0.4× 82 0.5× 9 0.1× 31 0.3× 42 445
Anne M. Hahn Germany 12 82 0.4× 58 0.3× 206 1.1× 9 0.1× 9 0.1× 23 437
Limin Yan China 11 21 0.1× 174 0.9× 107 0.6× 10 0.1× 47 0.4× 30 431

Countries citing papers authored by Ryan Sprissler

Since Specialization
Citations

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

Fields of papers citing papers by Ryan Sprissler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ryan Sprissler

This figure shows the co-authorship network connecting the top 25 collaborators of Ryan Sprissler. A scholar is included among the top collaborators of Ryan Sprissler 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 Ryan Sprissler. Ryan Sprissler 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
2.
Jergović, Mladen, Jennifer L. Uhrlaub, Makiko Watanabe, et al.. (2022). Competent immune responses to SARS-CoV-2 variants in older adults following two doses of mRNA vaccination. Nature Communications. 13(1). 2891–2891. 11 indexed citations
3.
Betancourt, Walter Q., Bradley W. Schmitz, Gabriel K. Innes, et al.. (2021). COVID-19 containment on a college campus via wastewater-based epidemiology, targeted clinical testing and an intervention. The Science of The Total Environment. 779. 146408–146408. 204 indexed citations breakdown →
4.
Snyder, Eric M., Ryan Sprissler, & Thomas P. Olson. (2021). The Importance of Use of Genetics to Guide Hypertension Therapy. 4. 117–125.
5.
Sprissler, Ryan, Laurel Johnstone, Hani M. Babiker, et al.. (2020). Rare Tumor-Normal Matched Whole Exome Sequencing Identifies Novel Genomic Pathogenic Germline and Somatic Aberrations. Cancers. 12(6). 1618–1618. 2 indexed citations
6.
Sprissler, Ryan, Robert W. Bina, Willard S. Kasoff, et al.. (2019). Leukocyte expression profiles reveal gene sets with prognostic value for seizure-free outcome following stereotactic laser amygdalohippocampotomy. Scientific Reports. 9(1). 1086–1086. 5 indexed citations
7.
Hammer, Michael F., Ryan Sprissler, Robert W. Bina, et al.. (2019). Altered expression of signaling pathways regulating neuronal excitability in hippocampal tissue of temporal lobe epilepsy patients with low and high seizure frequency. Epilepsy Research. 155. 106145–106145. 9 indexed citations
8.
Snyder, Eric M., et al.. (2019). Relationship Between a Weighted Multi‐Gene Algorithm and Blood Pressure Control in Hypertension. The FASEB Journal. 33(S1). 1 indexed citations
9.
Olson, Thomas P., et al.. (2019). The Effect of Genetically Guided Mathematical Prediction and the Blood Pressure Response to Pharmacotherapy in Hypertension Patients. Clinical Medicine Insights Cardiology. 13. 2771476219–2771476219.
10.
Sprissler, Ryan, et al.. (2019). Relationship between a Weighted Multi-Gene Algorithm and Blood Pressure Control in Hypertension. Journal of Clinical Medicine. 8(3). 289–289. 4 indexed citations
11.
Snyder, Eric M., et al.. (2018). Economic evaluation of a pharmacogenomic multi-gene panel test to optimize anti-hypertension therapy: simulation study. Journal of Medical Economics. 21(12). 1246–1253. 5 indexed citations
13.
Hammer, Michael F., Atsushi Ishii, Laurel Johnstone, et al.. (2017). Rare variants of small effect size in neuronal excitability genes influence clinical outcome in Japanese cases of SCN1A truncation-positive Dravet syndrome. PLoS ONE. 12(7). e0180485–e0180485. 18 indexed citations
14.
Sprissler, Ryan, Jacy L. Wagnon, Rosie Bunton-Stasyshyn, Miriam H. Meisler, & Michael F. Hammer. (2016). Altered gene expression profile in a mouse model of SCN8A encephalopathy. Experimental Neurology. 288. 134–141. 26 indexed citations
15.
Sprissler, Ryan, et al.. (2015). A problem not yet manifest: gaps in insurance coverage of medical interventions after genetic testing. Journal of Law and the Biosciences. 2(3). lsv043–lsv043. 2 indexed citations
16.
Anderson, Kirk E., et al.. (2013). Draft genome sequences of two Bifidobacterium sp. from the honey bee (Apis mellifera). Gut Pathogens. 5(1). 42–42. 22 indexed citations
17.
Veeramah, Krishna R., Laurel Johnstone, Tatiana M. Karafet, et al.. (2013). Exome sequencing reveals new causal mutations in children with epileptic encephalopathies. Epilepsia. 54(7). 1270–1281. 219 indexed citations
18.
Baker, Sarah E., Eric C. Wong, Courtney M. Wheatley, et al.. (2012). Genetic Variation of SCNN1A Influences Lung Diffusing Capacity in Cystic Fibrosis. Medicine & Science in Sports & Exercise. 44(12). 2315–2321. 7 indexed citations
19.
Wheatley, Courtney M., Hanna Phan, Asad E. Patanwala, et al.. (2011). Influence of Genetic variation of the β2-Adrenergic receptor on lung diffusion in patients with cystic fibrosis. Pulmonary Pharmacology & Therapeutics. 24(5). 610–616. 2 indexed citations
20.
Baker, Sarah E., et al.. (2011). Genetic variation of αENaC influences lung diffusion during exercise in humans. Respiratory Physiology & Neurobiology. 179(2-3). 212–218. 9 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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