Kate D. Meyer

10.9k total citations · 5 hit papers
37 papers, 8.1k citations indexed

About

Kate D. Meyer is a scholar working on Molecular Biology, Cancer Research and Electrical and Electronic Engineering. According to data from OpenAlex, Kate D. Meyer has authored 37 papers receiving a total of 8.1k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Molecular Biology, 14 papers in Cancer Research and 4 papers in Electrical and Electronic Engineering. Recurrent topics in Kate D. Meyer's work include RNA modifications and cancer (33 papers), Cancer-related gene regulation (15 papers) and RNA Research and Splicing (15 papers). Kate D. Meyer is often cited by papers focused on RNA modifications and cancer (33 papers), Cancer-related gene regulation (15 papers) and RNA Research and Splicing (15 papers). Kate D. Meyer collaborates with scholars based in United States, Germany and Australia. Kate D. Meyer's co-authors include Samie R. Jaffrey, Olivier Elemento, Yogesh Saletore, Christopher E. Mason, Paul Zumbo, Jun Zhou, Deepak P. Patil, Maxim A. Skabkin, Alexandra Zinoviev and Shu‐Bing Qian and has published in prestigious journals such as Cell, Nucleic Acids Research and Nature Communications.

In The Last Decade

Kate D. Meyer

35 papers receiving 8.0k citations

Hit Papers

Comprehensive Analysis of mRNA Methylation Reveals Enrich... 2012 2026 2016 2021 2012 2015 2017 2014 2019 1000 2.0k 3.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kate D. Meyer United States 21 7.8k 3.6k 1.1k 398 240 37 8.1k
Yogesh Saletore United States 6 5.1k 0.7× 2.4k 0.7× 764 0.7× 288 0.7× 158 0.7× 6 5.3k
Shalini Oberdoerffer United States 15 2.0k 0.3× 589 0.2× 30 0.0× 125 0.3× 40 0.2× 24 2.3k
Gerhard Mittler Germany 31 2.9k 0.4× 500 0.1× 39 0.0× 277 0.7× 62 0.3× 54 3.5k
Kathy Boon United States 25 1.8k 0.2× 304 0.1× 59 0.1× 220 0.6× 76 0.3× 40 2.8k
Paola Caiafa Italy 30 2.2k 0.3× 184 0.1× 102 0.1× 834 2.1× 60 0.3× 80 2.7k
Kirk B. Jensen United States 20 3.7k 0.5× 559 0.2× 32 0.0× 94 0.2× 42 0.2× 29 4.1k
Éva Forgács United States 21 1.7k 0.2× 256 0.1× 40 0.0× 267 0.7× 112 0.5× 39 2.4k
Zhe Ji China 27 2.7k 0.3× 633 0.2× 10 0.0× 318 0.8× 261 1.1× 121 3.7k
Kazuhiko Uchida Japan 26 1.0k 0.1× 227 0.1× 58 0.1× 647 1.6× 271 1.1× 76 2.0k

Countries citing papers authored by Kate D. Meyer

Since Specialization
Citations

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

Fields of papers citing papers by Kate D. Meyer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kate D. Meyer

This figure shows the co-authorship network connecting the top 25 collaborators of Kate D. Meyer. A scholar is included among the top collaborators of Kate D. 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 Kate D. Meyer. Kate D. Meyer 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.
Tegowski, Matthew & Kate D. Meyer. (2024). Studying m6A in the brain: a perspective on current methods, challenges, and future directions. Frontiers in Molecular Neuroscience. 17. 1393973–1393973. 5 indexed citations
2.
Flamand, Mathieu N. & Kate D. Meyer. (2024). Simultaneous profiling of the RNA targets of two RNA-binding proteins using TRIBE-STAMP. Methods in enzymology on CD-ROM/Methods in enzymology. 705. 127–157.
3.
Tegowski, Matthew, et al.. (2024). Single-cell m6A profiling in the mouse brain uncovers cell type-specific RNA methylomes and age-dependent differential methylation. Nature Neuroscience. 27(12). 2512–2520. 7 indexed citations
4.
Thompson, Matthew G., et al.. (2024). Programmable protein expression using a genetically encoded m6A sensor. Nature Biotechnology. 42(9). 1417–1428. 12 indexed citations
5.
Lee, Sungmin, Clément Carré, André Fischer, et al.. (2023). Exploring the brain epitranscriptome: perspectives from the NSAS summit. Frontiers in Neuroscience. 17. 1291446–1291446. 2 indexed citations
6.
Leung, Sara W., Ayan Banerjee, Derrick J. Morton, et al.. (2023). The Drosophila Nab2 RNA binding protein inhibits m6A methylation and male-specific splicing of Sex lethal transcript in female neuronal tissue. eLife. 12. 5 indexed citations
7.
Meyer, Kate D., et al.. (2023). In situ visualization of m6A sites in cellular mRNAs. Nucleic Acids Research. 51(20). e101–e101. 22 indexed citations
8.
Tegowski, Matthew, Mathieu N. Flamand, & Kate D. Meyer. (2022). scDART-seq reveals distinct m6A signatures and mRNA methylation heterogeneity in single cells. Molecular Cell. 82(4). 868–878.e10. 112 indexed citations
9.
Flamand, Mathieu N., et al.. (2022). Single-molecule identification of the target RNAs of different RNA binding proteins simultaneously in cells. Genes & Development. 36(17-18). 1002–1015. 25 indexed citations
10.
Holley, Christopher L., et al.. (2022). Improved Methods for Deamination-Based m6A Detection. Frontiers in Cell and Developmental Biology. 10. 888279–888279. 7 indexed citations
11.
Choi, Seung Hyuk, Mathieu N. Flamand, Bei Liu, et al.. (2022). RBM45 is an m6A-binding protein that affects neuronal differentiation and the splicing of a subset of mRNAs. Cell Reports. 40(9). 111293–111293. 22 indexed citations
12.
Meyer, Kate D.. (2022). How m6A makes its mark. Nature Reviews Molecular Cell Biology. 23(8). 519–519. 5 indexed citations
13.
Gallon, John, et al.. (2021). Mapping of m6A and Its Regulatory Targets in Prostate Cancer Reveals a METTL3-Low Induction of Therapy Resistance. Molecular Cancer Research. 19(8). 1398–1411. 21 indexed citations
14.
Tegowski, Matthew, et al.. (2021). Detecting m6A with In Vitro DART-Seq. Methods in molecular biology. 2404. 363–374. 3 indexed citations
15.
Meyer, Kate D.. (2019). DART-seq: an antibody-free method for global m6A detection. Nature Methods. 16(12). 1275–1280. 327 indexed citations breakdown →
16.
Flamand, Mathieu N. & Kate D. Meyer. (2019). The epitranscriptome and synaptic plasticity. Current Opinion in Neurobiology. 59. 41–48. 37 indexed citations
17.
Liu, Bei, Dawn K. Merriman, Seung Hyuk Choi, et al.. (2018). A potentially abundant junctional RNA motif stabilized by m6A and Mg2+. Nature Communications. 9(1). 2761–2761. 58 indexed citations
18.
Meyer, Kate D. & Samie R. Jaffrey. (2016). Expanding the diversity of DNA base modifications with N 6-methyldeoxyadenosine. Genome biology. 17(1). 5–5. 11 indexed citations
19.
Meyer, Kate D., Deepak P. Patil, Jun Zhou, et al.. (2015). 5′ UTR m6A Promotes Cap-Independent Translation. Cell. 163(4). 999–1010. 1432 indexed citations breakdown →
20.
Meyer, Kate D. & Jill A. Morris. (2008). Immunohistochemical analysis of Disc1 expression in the developing and adult hippocampus. Gene Expression Patterns. 8(7-8). 494–501. 27 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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