Erik Arner

3.5k citations
24 papers · 668 · h-index 15

Impact in

    • Genomics and Chromatin Dynamics
    • RNA Research and Splicing
    • RNA modifications and cancer
    • Epigenetics and DNA Methylation
    • Advanced biosensing and bioanalysis techniques
    • Cancer-related molecular mechanisms research

Papers in

    • Genomics and Chromatin Dynamics 6
    • RNA Research and Splicing 5
    • RNA and protein synthesis mechanisms 3
    • Pluripotent Stem Cells Research 2

Erik Arner

23 papers receiving 661 citations

Peers

Erik Arner
Comparison fields: 5 of 104
  • Molecular Biology 400
  • Cancer Research 76
  • Immunology 82
  • Cell Biology 41
  • Genetics 64
Replace Weiwei Guo with:
Weiwei Guo China
Frida Danielsson Sweden
Brian E. Fee United States
Ashley J. Waardenberg Australia
Naomi R. Genuth United States
Alla V. Ivanova United States
Anastasiya Boltengagen Germany
Xiaoling Wan China
Andrey L. Karamyshev United States
Nari Kim South Korea
Erik Arner relative to Weiwei Guo China Weiwei Guo's profile →
Citations per field
00.5×1.5×
Weiwei Guo · 1×
Citations per year

Countries citing papers authored by Erik Arner

Since Specialization
Citations

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

Fields of papers citing papers by Erik Arner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201796
2 200977
3 201172
4 200961
5 201550
6 202241
7 201539
8 201132
9 201032
10 201930
11 201421
12 201920
13 202118
14 202317
15 201616
16 202110
17 20099
18 20188
19 20217
20 20195

About Erik Arner

Erik Arner is a scholar working on Molecular Biology, Epidemiology, Physiology, Genetics and Cancer Research, having authored 24 papers that have together received 668 indexed citations. Recurring topics across this work include Genomics and Chromatin Dynamics (6 papers), RNA Research and Splicing (5 papers), Adipose Tissue and Metabolism (3 papers), RNA and protein synthesis mechanisms (3 papers), Cancer-related molecular mechanisms research (3 papers), Pluripotent Stem Cells Research (2 papers), Lymphatic System and Diseases (2 papers) and Computational Drug Discovery Methods (2 papers). The work is most often cited by research in Molecular Biology (400 citations), Cancer Research (76 citations), Immunology (82 citations), Cell Biology (41 citations) and Genetics (64 citations). Erik Arner has collaborated with scholars based in Japan, Sweden and Australia. Frequent co-authors include Carsten O. Daub, Yoshihide Hayashizaki, Piero Carninci, Harukazu Suzuki, Michiel de Hoon, Alistair R. R. Forrest, Yoshihide Hayashizaki, Hideya Kawaji, Timo Lassmann and Masayoshi Itoh. Their work appears in journals such as PLoS Computational Biology, Bioinformatics, Genome biology, Scientific Reports and Blood.

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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