Matthew J. Payea

426 citations
16 papers · 232 · h-index 8

Impact in

    • RNA modifications and cancer
    • RNA and protein synthesis mechanisms
    • RNA Research and Splicing
    • Circular RNAs in diseases
    • Genomics and Phylogenetic Studies
    • Cancer-related gene regulation

Papers in

    • RNA modifications and cancer 8
    • RNA and protein synthesis mechanisms 7
    • RNA Research and Splicing 6
    • RNA Interference and Gene Delivery 2
    • Telomeres, Telomerase, and Senescence 5

Matthew J. Payea

16 papers receiving 230 citations

Peers

Matthew J. Payea
Comparison fields: 5 of 54
  • Aging 6
  • Molecular Biology 183
  • Cancer Research 37
  • Physiology 31
  • Geriatrics and Gerontology 2
Replace Benoît Albaud with:
Benoît Albaud France
Fiona Chang Australia
Jenny F. Nathans United States
Guang Peng China
Lumeng Jia China
Nadine Übelmesser Germany
Maria Azkanaz Netherlands
Anukana Bhattacharjee United States
Julienne J. O’Rourke Australia
Fan Hu China
Matthew J. Payea relative to Benoît Albaud France Benoît Albaud's profile →
Citations per field
00.5×4.2×
Benoît Albaud · 1×
Citations per year

Countries citing papers authored by Matthew J. Payea

Since Specialization
Citations

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

Fields of papers citing papers by Matthew J. Payea

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Matthew J. Payea, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Matthew J. Payea Line = papers co-authored together Matthew J. Payea links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 201453
2 202042
3 202040
4 202221
5 201917
6 201716
7 202412
8 201410
9 20237
10 20233
11 20243
12 20153
13 20242
14 20221
15 20221
16 20241

About Matthew J. Payea

Matthew J. Payea is a scholar working on Molecular Biology, Physiology, Cell Biology, Spectroscopy and Aging, having authored 16 papers that have together received 232 indexed citations. Recurring topics across this work include RNA modifications and cancer (8 papers), RNA and protein synthesis mechanisms (7 papers), RNA Research and Splicing (6 papers), Telomeres, Telomerase, and Senescence (5 papers), Advanced Proteomics Techniques and Applications (2 papers), Genetics, Aging, and Longevity in Model Organisms (2 papers), Biotin and Related Studies (2 papers) and RNA Interference and Gene Delivery (2 papers). The work is most often cited by research in Aging (6 citations), Molecular Biology (183 citations), Cancer Research (37 citations), Physiology (31 citations) and Geriatrics and Gerontology (2 citations). Matthew J. Payea has collaborated with scholars based in United States, Czechia and Belgium. Frequent co-authors include Myriam Gorospe, Carlos Anerillas, Eric M. Phizicky, Ravi Tharakan, Michael P. Guy, William F. Heinz, Stuart F.J. Le Grice, Yoshiko Kon, Jason W. Rausch and Xiaoju Zhang. Their work appears in journals such as Journal of Visualized Experiments, RNA, eLife, Nature Communications and Molecular Cell.

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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