Erik Arner

3.4k total citations
24 papers, 636 citations indexed

About

Erik Arner is a scholar working on Molecular Biology, Physiology and Cancer Research. According to data from OpenAlex, Erik Arner has authored 24 papers receiving a total of 636 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 4 papers in Physiology and 4 papers in Cancer Research. Recurrent topics in Erik Arner's work include Genomics and Chromatin Dynamics (9 papers), RNA Research and Splicing (8 papers) and Adipose Tissue and Metabolism (4 papers). Erik Arner is often cited by papers focused on Genomics and Chromatin Dynamics (9 papers), RNA Research and Splicing (8 papers) and Adipose Tissue and Metabolism (4 papers). Erik Arner collaborates with scholars based in Japan, Sweden and Australia. Erik Arner's co-authors include Carsten O. Daub, Yoshihide Hayashizaki, Piero Carninci, Harukazu Suzuki, Michiel de Hoon, Yoshihide Hayashizaki, Alistair R. R. Forrest, Masayoshi Itoh, Timo Lassmann and Hideya Kawaji and has published in prestigious journals such as Nucleic Acids Research, Blood and Bioinformatics.

In The Last Decade

Erik Arner

23 papers receiving 631 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Erik Arner Japan 15 421 89 83 70 67 24 636
Zhouchun Shang China 13 585 1.4× 66 0.7× 114 1.4× 98 1.4× 59 0.9× 19 801
Thanasis Margaritis Netherlands 17 947 2.2× 89 1.0× 131 1.6× 113 1.6× 69 1.0× 26 1.2k
Daniel Osorio United States 13 527 1.3× 112 1.3× 68 0.8× 54 0.8× 20 0.3× 30 748
Patrick Ng Singapore 10 719 1.7× 198 2.2× 113 1.4× 68 1.0× 85 1.3× 14 1.0k
Kaur Alasoo Estonia 12 545 1.3× 155 1.7× 65 0.8× 259 3.7× 39 0.6× 19 857
Elena Chiavacci Italy 12 508 1.2× 70 0.8× 97 1.2× 69 1.0× 16 0.2× 18 805
Alla V. Ivanova United States 18 472 1.1× 66 0.7× 80 1.0× 49 0.7× 15 0.2× 41 937
Martin Del Castillo Velasco‐Herrera United Kingdom 9 925 2.2× 71 0.8× 63 0.8× 161 2.3× 24 0.4× 14 1.1k
Dario Besusso Italy 17 533 1.3× 312 3.5× 58 0.7× 82 1.2× 91 1.4× 31 1.0k
Manish Sharma United States 14 447 1.1× 134 1.5× 49 0.6× 44 0.6× 31 0.5× 32 856

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-authorship network of co-authors of Erik Arner

This figure shows the co-authorship network connecting the top 25 collaborators of Erik Arner. A scholar is included among the top collaborators of Erik Arner 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 Erik Arner. Erik Arner 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.
Arakawa, Takahiro, Masaaki Furuno, Harukazu Suzuki, et al.. (2023). xcore: an R package for inference of gene expression regulators. BMC Bioinformatics. 24(1). 14–14.
2.
Reitzner, Stefan Markus, Muhammad Arif, Bogumił Kaczkowski, et al.. (2023). Molecular profiling of high-level athlete skeletal muscle after acute endurance or resistance exercise – A systems biology approach. Molecular Metabolism. 79. 101857–101857. 14 indexed citations
3.
Pillon, Nicolas J., Jonathon A. B. Smith, Petter S. Alm, et al.. (2022). Distinctive exercise-induced inflammatory response and exerkine induction in skeletal muscle of people with type 2 diabetes. Science Advances. 8(36). eabo3192–eabo3192. 35 indexed citations
4.
Umarov, Ramzan, et al.. (2021). ReFeaFi: Genome-wide prediction of regulatory elements driving transcription initiation. PLoS Computational Biology. 17(9). e1009376–e1009376. 6 indexed citations
5.
Umarov, Ramzan, Yu Li, & Erik Arner. (2021). DeepCellState: An autoencoder-based framework for predicting cell type specific transcriptional states induced by drug treatment. PLoS Computational Biology. 17(10). e1009465–e1009465. 8 indexed citations
6.
Napolitano, Francesco, Patrizia Annunziata, Akira Hasegawa, et al.. (2021). Automatic identification of small molecules that promote cell conversion and reprogramming. Stem Cell Reports. 16(5). 1381–1390. 17 indexed citations
7.
Bonetti, Alessandro, Andrew Tae-Jun Kwon, Erik Arner, & Piero Carninci. (2021). Analysis of Enhancer–Promoter Interactions using CAGE and RADICL-Seq Technologies. Methods in molecular biology. 2351. 201–210. 1 indexed citations
8.
Castillejo-López, Casimiro, Milos Pjanic, Susanne Hetty, et al.. (2019). Detailed Functional Characterization of a Waist-Hip Ratio Locus in 7p15.2 Defines an Enhancer Controlling Adipocyte Differentiation. iScience. 20. 42–59. 5 indexed citations
9.
Kulyté, Agné, Kelvin H. M. Kwok, Michiel de Hoon, et al.. (2019). MicroRNA-27a/b-3p and PPARG regulate SCAMP3 through a feed- forward loop during adipogenesis. Scientific Reports. 9(1). 13891–13891. 19 indexed citations
10.
Huang, Yi, Masaaki Furuno, Takahiro Arakawa, et al.. (2019). A framework for identification of on- and off-target transcriptional responses to drug treatment. Scientific Reports. 9(1). 17603–17603. 28 indexed citations
11.
Baillie, J. Kenneth, Erik Arner, Carsten O. Daub, et al.. (2017). Analysis of the human monocyte-derived macrophage transcriptome and response to lipopolysaccharide provides new insights into genetic aetiology of inflammatory bowel disease. PLoS Genetics. 13(3). e1006641–e1006641. 94 indexed citations
12.
Klein, Sarah, Lothar C. Dieterich, Anthony Mathelier, et al.. (2016). DeepCAGE transcriptomics identify HOXD10 as a transcription factor regulating lymphatic endothelial responses to VEGF-C. Journal of Cell Science. 129(13). 2573–2585. 16 indexed citations
13.
Aitken, Stuart, Ahmad M. N. Alhendi, Masayoshi Itoh, et al.. (2015). Transcriptional Dynamics Reveal Critical Roles for Non-coding RNAs in the Immediate-Early Response. PLoS Computational Biology. 11(4). e1004217–e1004217. 46 indexed citations
14.
Dieterich, Lothar C., Sarah Klein, Anthony Mathelier, et al.. (2015). DeepCAGE Transcriptomics Reveal an Important Role of the Transcription Factor MAFB in the Lymphatic Endothelium. Cell Reports. 13(7). 1493–1504. 38 indexed citations
15.
Kimura, Yasumasa, Michiel de Hoon, Yuri Ishizu, et al.. (2011). Optimization of turn-back primers in isothermal amplification. Nucleic Acids Research. 39(9). e59–e59. 70 indexed citations
16.
Franzén, Oscar, Erik Arner, Marcela Ferella, et al.. (2011). The Short Non-Coding Transcriptome of the Protozoan Parasite Trypanosoma cruzi. PLoS neglected tropical diseases. 5(8). e1283–e1283. 32 indexed citations
17.
Kratz, Anton, Erik Arner, Rintaro Saito, et al.. (2010). Core promoter structure and genomic context reflect histone 3 lysine 9 acetylation patterns. BMC Genomics. 11(1). 257–257. 31 indexed citations
18.
Akalin, Altuna, David Fredman, Erik Arner, et al.. (2009). Transcriptional features of genomic regulatory blocks. Genome biology. 10(4). R38–R38. 75 indexed citations
19.
Kubosaki, Atsutaka, Yasuhiro Tomaru, Michihira Tagami, et al.. (2009). Genome-wide investigation of in vivoEGR-1 binding sites in monocytic differentiation. Genome biology. 10(4). R41–R41. 59 indexed citations
20.
Arner, Erik, Yoshihide Hayashizaki, & Carsten O. Daub. (2009). NGSView: an extensible open source editor for next-generation sequencing data. Bioinformatics. 26(1). 125–126. 9 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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