Matthew R. Meyer

2.6k total citations · 1 hit paper
21 papers, 878 citations indexed

About

Matthew R. Meyer is a scholar working on Molecular Biology, Physiology and Psychiatry and Mental health. According to data from OpenAlex, Matthew R. Meyer has authored 21 papers receiving a total of 878 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 9 papers in Physiology and 9 papers in Psychiatry and Mental health. Recurrent topics in Matthew R. Meyer's work include Dementia and Cognitive Impairment Research (9 papers), Alzheimer's disease research and treatments (8 papers) and Plant Reproductive Biology (4 papers). Matthew R. Meyer is often cited by papers focused on Dementia and Cognitive Impairment Research (9 papers), Alzheimer's disease research and treatments (8 papers) and Plant Reproductive Biology (4 papers). Matthew R. Meyer collaborates with scholars based in United States, Australia and Singapore. Matthew R. Meyer's co-authors include Richard K. Wilson, Petra Erdmann-Gilmore, David H. Spencer, R. Reid Townsend, Tamara Lamprecht, David A. Russler‐Germain, Margaret A. Young, Robert S. Fulton, Chris Miller and T J Ley and has published in prestigious journals such as Journal of Biological Chemistry, Blood and PLoS ONE.

In The Last Decade

Matthew R. Meyer

20 papers receiving 858 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A blood-based diagnostic test incorporating plasma Aβ42/40 ratio, ApoE proteotype, and age accurately identifies brain amyloid status: findings from a multi cohort validity analysis

2021 136 citations Tim West, Kristopher M. Kirmess et al. Molecular Neurodegeneration profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Matthew R. Meyer United States	13	496	277	238	187	76	21	878
Klaus Huber Austria	13	160 0.3×	59 0.2×	205 0.9×	21 0.1×	27 0.4×	23	551
Anahita Bhathena United States	16	309 0.6×	42 0.2×	46 0.2×	45 0.2×	54 0.7×	33	728
Anne N. Shemon Australia	14	266 0.5×	30 0.1×	63 0.3×	137 0.7×	16 0.2×	16	1.0k
Anita Chamba United Kingdom	12	253 0.5×	39 0.1×	100 0.4×	73 0.4×	35 0.5×	19	742
Pamela Kell United States	12	188 0.4×	45 0.2×	181 0.8×	26 0.1×	36 0.5×	19	474
Matthew Metcalf United States	11	231 0.5×	158 0.6×	84 0.4×	17 0.1×	66 0.9×	19	786
Puneet Anand United States	11	356 0.7×	19 0.1×	266 1.1×	22 0.1×	63 0.8×	23	777
Benjamín Rodríguez‐Santiago Spain	19	523 1.1×	12 0.0×	79 0.3×	29 0.2×	86 1.1×	39	1.0k
Péter Ugocsai Germany	15	246 0.5×	51 0.2×	56 0.2×	14 0.1×	35 0.5×	23	558
Mylène Pouliot Canada	15	177 0.4×	35 0.1×	53 0.2×	49 0.3×	36 0.5×	39	606

Countries citing papers authored by Matthew R. Meyer

Since Specialization

Citations

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

Fields of papers citing papers by Matthew R. Meyer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew R. Meyer. 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 Matthew R. Meyer. The network helps show where Matthew R. Meyer may publish in the future.

Co-authorship network of co-authors of Matthew R. Meyer

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew R. Meyer. A scholar is included among the top collaborators of Matthew R. Meyer 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 Matthew R. Meyer. Matthew R. Meyer 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

Masedunskas, Andrius, Giovanna Petrucci, Valeria Tosti, et al.. (2025). Prolonged fasting promotes systemic inflammation and platelet activation in humans: A medically supervised, water-only fasting and refeeding study. Molecular Metabolism. 96. 102152–102152. 5 indexed citations

Cody, Karly Alex, Lianlian Du, Rachel Studer, et al.. (2025). Accuracy of plasma biomarkers to detect Alzheimer's disease proteinopathy prior to dementia. Alzheimer s & Dementia. 21(3). e14570–e14570. 4 indexed citations

Fogelman, I., Tim West, Joel B. Braunstein, et al.. (2023). Independent study demonstrates amyloid probability score accurately indicates amyloid pathology. Annals of Clinical and Translational Neurology. 10(5). 765–778. 13 indexed citations

Cook, Jesse D., David T. Plante, Derek Norton, et al.. (2023). Associations of sleep duration and daytime sleepiness with plasma amyloid beta and cognitive performance in cognitively unimpaired, middle-aged and older African Americans. SLEEP. 47(1). 4 indexed citations

Cooley, Sarah, Anna H. Boerwinkle, Kevin E. Yarasheski, et al.. (2023). Plasma Aβ42/Aβ40 Ratios in Older People With Human Immunodeficiency Virus. Clinical Infectious Diseases. 76(10). 1776–1783. 4 indexed citations

Rissman, Robert A., Oliver Langford, Rema Raman, et al.. (2023). Plasma Aβ42/Aβ40 and phospho‐tau217 concentration ratios increase the accuracy of amyloid PET classification in preclinical Alzheimer's disease. Alzheimer s & Dementia. 20(2). 1214–1224. 64 indexed citations

Palmqvist, Sebastian, Pontus Tideman, Joel B. Braunstein, et al.. (2023). Blood Biomarkers Improve The Diagnostic Accuracy Of Alzheimer’s Disease As Compared With Current Diagnostic Standard In the Primary Care Setting. Alzheimer s & Dementia. 19(S15). 2 indexed citations

Aschenbrenner, Andrew J., Yan Li, Rachel L. Henson, et al.. (2022). Comparison of plasma and CSF biomarkers in predicting cognitive decline. Annals of Clinical and Translational Neurology. 9(11). 1739–1751. 28 indexed citations

Meyer, Matthew R., Kristopher M. Kirmess, Mary S. Holubasch, et al.. (2022). Plasma ratio of phospho‐ to non‐phospho‐tau at threonine 217 identifies brain amyloid burden as measured by quantitative amyloid PET in the PARIS sub‐study of IDEAS. Alzheimer s & Dementia. 18(S6).

10.

Kirmess, Kristopher M., Matthew R. Meyer, Mary S. Holubasch, et al.. (2021). The PrecivityAD™ test: Accurate and reliable LC-MS/MS assays for quantifying plasma amyloid beta 40 and 42 and apolipoprotein E proteotype for the assessment of brain amyloidosis. Clinica Chimica Acta. 519. 267–275. 73 indexed citations

11.

West, Tim, Kristopher M. Kirmess, Matthew R. Meyer, et al.. (2021). A blood-based diagnostic test incorporating plasma Aβ42/40 ratio, ApoE proteotype, and age accurately identifies brain amyloid status: findings from a multi cohort validity analysis. Molecular Neurodegeneration. 16(1). 30–30. 136 indexed citations breakdown →

12.

Wilson, Margaret E., Shin‐Cheng Tzeng, Megan M. Augustin, et al.. (2021). Quantitative Proteomics and Phosphoproteomics Support a Role for Mut9-Like Kinases in Multiple Metabolic and Signaling Pathways in Arabidopsis. Molecular & Cellular Proteomics. 20. 100063–100063. 14 indexed citations

13.

Burel, Sophie, Matthew R. Meyer, Cheryl F. Lichti, et al.. (2017). C-terminal phosphorylation of NaV1.5 impairs FGF13-dependent regulation of channel inactivation. Journal of Biological Chemistry. 292(42). 17431–17448. 20 indexed citations

14.

Meyer, Matthew R., Shweta Shah, & A. Gururaj Rao. (2017). Investigation of Autophosphorylation Sites of Plant Receptor Kinases and Phosphorylation of Interacting Partners. Methods in molecular biology. 1621. 121–130. 1 indexed citations

15.

Czyzewicz, Nathan, Natalia Nikonorova, Matthew R. Meyer, et al.. (2016). The growing story of (ARABIDOPSIS) CRINKLY 4. Journal of Experimental Botany. 67(16). 4835–4847. 21 indexed citations

16.

Meyer, Matthew R., Shweta Shah, Jingyi Zhang, Henry W. Rohrs, & A. Gururaj Rao. (2015). Evidence for Intermolecular Interactions between the Intracellular Domains of the Arabidopsis Receptor-Like Kinase ACR4, Its Homologs and the Wox5 Transcription Factor. PLoS ONE. 10(3). e0118861–e0118861. 20 indexed citations

17.

Russler‐Germain, David A., David H. Spencer, Margaret A. Young, et al.. (2014). The R882H DNMT3A Mutation Associated with AML Dominantly Inhibits Wild-Type DNMT3A by Blocking Its Ability to Form Active Tetramers. Cancer Cell. 25(4). 442–454. 316 indexed citations

18.

Meyer, Matthew R., Shweta Shah, & A. Gururaj Rao. (2013). Insights into molecular interactions between the juxtamembrane and kinase subdomains of the Arabidopsis Crinkly-4 receptor-like kinase. Archives of Biochemistry and Biophysics. 535(2). 101–110. 9 indexed citations

19.

Klco, Jeffery M., David H. Spencer, Tamara Lamprecht, et al.. (2013). Genomic impact of transient low-dose decitabine treatment on primary AML cells. Blood. 121(9). 1633–1643. 106 indexed citations

20.

Meyer, Matthew R., Cheryl F. Lichti, R. Reid Townsend, & A. Gururaj Rao. (2011). Identification of in Vitro Autophosphorylation Sites and Effects of Phosphorylation on the Arabidopsis CRINKLY4 (ACR4) Receptor-like Kinase Intracellular Domain: Insights into Conformation, Oligomerization, and Activity. Biochemistry. 50(12). 2170–2186. 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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