Rachel Munk

4.1k citations
49 papers · 2.7k indexed · 1 hit paper · h-index 23

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
  • Aging top 5%

Papers in

    • MicroRNA in disease regulation 13
    • Cancer-related molecular mechanisms research 11
    • Telomeres, Telomerase, and Senescence 14

Rachel Munk

47 papers receiving 2.7k citations

Hit Papers

Identification of HuR target circular RNAs uncovers suppression of PABPN1 translation by CircPABPN1 2017 · 658 citations
6582017202620202023200400600

Peers

Rachel Munk
Comparison fields: 5 of 104
  • Cancer Research 1.6k
  • Aging 80
  • Molecular Biology 2.2k
  • Physiology 407
  • Immunology 289
Replace Sugiko Watanabe with:
Sugiko Watanabe Japan
Christopher F. Bennett United States
Samah Shah United States
Brian C. Capell United States
Yavuz Oktay Türkiye
Eun Joo Lee South Korea
Cleo L. Bishop United Kingdom
Seung‐Yoon Park South Korea
Zoltán Wiener Hungary
Mohamed Nemir Switzerland
Rachel Munk relative to Sugiko Watanabe Japan Sugiko Watanabe's profile →
Citations per field
00.5×1.5×2.5×
Sugiko Watanabe · 1×
Citations per year

Countries citing papers authored by Rachel Munk

Since Specialization
Citations

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

Fields of papers citing papers by Rachel Munk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Rachel Munk, 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 Rachel Munk Line = papers co-authored together Rachel Munk links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20246
2 202410
3 202311
4 202333
5 20235
6 20226
7 202227
8 202264
9 202219
10 202211
11 202118
12 202119
13 20203
14 202051
15 202075
16 2019243
17 201910
18 2016201
19 2016183
20 20129

About Rachel Munk

Rachel Munk is a scholar working on Cancer Research, Physiology, Molecular Biology, Aging and Immunology, having authored 49 papers that have together received 2.7k indexed citations. Recurring topics across this work include RNA Research and Splicing (17 papers), Telomeres, Telomerase, and Senescence (14 papers), MicroRNA in disease regulation (13 papers), RNA modifications and cancer (12 papers), Circular RNAs in diseases (11 papers), Cancer-related molecular mechanisms research (11 papers), Mitochondrial Function and Pathology (5 papers) and RNA regulation and disease (5 papers). The work is most often cited by research in Cancer Research (1.6k citations), Aging (80 citations), Molecular Biology (2.2k citations), Physiology (407 citations) and Immunology (289 citations). Rachel Munk has collaborated with scholars based in United States, Italy and South Korea. Frequent co-authors include Myriam Gorospe, Kotb Abdelmohsen, Supriyo De, Amaresh C. Panda, Ioannis Grammatikakis, Kyoung Mi Kim, Jennifer L. Martindale, Dawood B. Dudekula, Ji Heon Noh and Yulan Piao. Their work appears in journals such as Nucleic Acids Research, PLoS ONE, Aging, Wiley Interdisciplinary Reviews - RNA and Aging 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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