Cosmas D. Arnold

3.5k total citations · 1 hit paper
22 papers, 2.1k citations indexed

About

Cosmas D. Arnold is a scholar working on Molecular Biology, Immunology and Plant Science. According to data from OpenAlex, Cosmas D. Arnold has authored 22 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 3 papers in Immunology and 3 papers in Plant Science. Recurrent topics in Cosmas D. Arnold's work include Genomics and Chromatin Dynamics (11 papers), RNA and protein synthesis mechanisms (8 papers) and RNA Research and Splicing (5 papers). Cosmas D. Arnold is often cited by papers focused on Genomics and Chromatin Dynamics (11 papers), RNA and protein synthesis mechanisms (8 papers) and RNA Research and Splicing (5 papers). Cosmas D. Arnold collaborates with scholars based in Austria, United States and Germany. Cosmas D. Arnold's co-authors include Alexander Stark, Martina Rath, Łukasz M. Boryń, Daniel Gerlach, Christoph Stelzer, Michaela Pagani, Ian Hodgson, Katharina Schernhuber, Muhammad A. Zabidi and Olga Frank and has published in prestigious journals such as Nature, Science and Nature Genetics.

In The Last Decade

Cosmas D. Arnold

22 papers receiving 2.1k citations

Hit Papers

Genome-Wide Quantitative Enhancer Activity Maps Identifie... 2013 2026 2017 2021 2013 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Cosmas D. Arnold Austria 15 1.9k 413 369 111 96 22 2.1k
Erica Larschan United States 23 2.0k 1.1× 624 1.5× 499 1.4× 74 0.7× 141 1.5× 46 2.2k
Marco Blanchette United States 27 2.0k 1.1× 268 0.6× 348 0.9× 112 1.0× 155 1.6× 37 2.3k
Miguel A. Moreno-Mateos Spain 16 1.6k 0.8× 260 0.6× 268 0.7× 66 0.6× 127 1.3× 22 1.8k
Nicolas Nègre France 25 2.1k 1.1× 339 0.8× 534 1.4× 121 1.1× 89 0.9× 51 2.4k
Paul E. Mains Canada 28 1.8k 0.9× 407 1.0× 284 0.8× 133 1.2× 77 0.8× 53 2.6k
Yurii Sedkov United States 20 1.7k 0.9× 285 0.7× 286 0.8× 88 0.8× 188 2.0× 24 1.9k
Takao Ishidate United States 19 1.9k 1.0× 247 0.6× 330 0.9× 77 0.7× 111 1.2× 26 2.3k
Nicholas J. Brideau United States 7 1.2k 0.7× 410 1.0× 244 0.7× 37 0.3× 99 1.0× 7 1.5k
Aleksandar Vojta Croatia 18 1.2k 0.7× 223 0.5× 197 0.5× 162 1.5× 59 0.6× 34 1.4k
Shinpei Kawaoka Japan 18 1.1k 0.6× 396 1.0× 577 1.6× 191 1.7× 97 1.0× 35 1.6k

Countries citing papers authored by Cosmas D. Arnold

Since Specialization
Citations

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

Fields of papers citing papers by Cosmas D. Arnold

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cosmas D. Arnold

This figure shows the co-authorship network connecting the top 25 collaborators of Cosmas D. Arnold. A scholar is included among the top collaborators of Cosmas D. Arnold 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 Cosmas D. Arnold. Cosmas D. Arnold 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.
Datlinger, Paul, Cosmas D. Arnold, Jenny Lin, et al.. (2025). Systematic discovery of CRISPR-boosted CAR T cell immunotherapies. Nature. 646(8086). 963–972. 3 indexed citations
2.
Datlinger, Paul, Cosmas D. Arnold, Jenny Lin, et al.. (2024). Engineering Next-Generation CAR T Cells Via Genetic Screens. Blood. 144(Supplement 1). 7151–7151. 1 indexed citations
3.
Kienle, Eike, Martin Oti, María Méndez-Lago, et al.. (2023). An unbiased AAV-STARR-seq screen revealing the enhancer activity map of genomic regions in the mouse brain in vivo. Scientific Reports. 13(1). 6745–6745. 10 indexed citations
4.
Neumayr, Christoph, Vanja Haberle, Leonid Serebreni, et al.. (2022). Differential cofactor dependencies define distinct types of human enhancers. Nature. 606(7913). 406–413. 55 indexed citations
5.
Neumayr, Christoph, Michaela Pagani, Alexander Stark, & Cosmas D. Arnold. (2019). STARR‐seq and UMI‐STARR‐seq: Assessing Enhancer Activities for Genome‐Wide‐, High‐, and Low‐Complexity Candidate Libraries. Current Protocols in Molecular Biology. 128(1). e105–e105. 43 indexed citations
6.
Haberle, Vanja, Cosmas D. Arnold, Michaela Pagani, et al.. (2019). Transcriptional cofactors display specificity for distinct types of core promoters. Nature. 570(7759). 122–126. 93 indexed citations
7.
Arnold, Cosmas D., Ashley R. Woodfin, Sebastian Wienerroither, et al.. (2018). A high‐throughput method to identify trans‐activation domains within transcription factor sequences. The EMBO Journal. 37(16). 44 indexed citations
8.
Muerdter, Felix, Łukasz M. Boryń, Ashley R. Woodfin, et al.. (2017). qPCR assay to measure ISG expression in human cells. Protocol Exchange. 1 indexed citations
9.
Muerdter, Felix, Łukasz M. Boryń, Ashley R. Woodfin, et al.. (2017). STARR-seq Screening protocol. Protocol Exchange. 1 indexed citations
10.
Muerdter, Felix, Łukasz M. Boryń, Ashley R. Woodfin, et al.. (2017). Resolving systematic errors in widely used enhancer activity assays in human cells. Nature Methods. 15(2). 141–149. 107 indexed citations
11.
Muerdter, Felix, Łukasz M. Boryń, Ashley R. Woodfin, et al.. (2017). STARR-seq Library Preparation. Protocol Exchange. 1 indexed citations
12.
Arnold, Cosmas D., Muhammad A. Zabidi, Michaela Pagani, et al.. (2016). Genome-wide assessment of sequence-intrinsic enhancer responsiveness at single-base-pair resolution. Nature Biotechnology. 35(2). 136–144. 61 indexed citations
13.
Muerdter, Felix, Łukasz M. Boryń, & Cosmas D. Arnold. (2015). STARR-seq — Principles and applications. Genomics. 106(3). 145–150. 70 indexed citations
14.
Shlyueva, Daria, Christoph Stelzer, Daniel Gerlach, et al.. (2014). Hormone-Responsive Enhancer-Activity Maps Reveal Predictive Motifs, Indirect Repression, and Targeting of Closed Chromatin. Molecular Cell. 54(1). 180–192. 97 indexed citations
15.
Zabidi, Muhammad A., Cosmas D. Arnold, Katharina Schernhuber, et al.. (2014). Enhancer–core-promoter specificity separates developmental and housekeeping gene regulation. Nature. 518(7540). 556–559. 314 indexed citations
16.
Yáñez-Cuna, J. Omar, Cosmas D. Arnold, Gerald Stampfel, et al.. (2014). Dissection of thousands of cell type-specific enhancers identifies dinucleotide repeat motifs as general enhancer features. Genome Research. 24(7). 1147–1156. 106 indexed citations
17.
Arnold, Cosmas D., Daniel Gerlach, Daniel Spies, et al.. (2014). Quantitative genome-wide enhancer activity maps for five Drosophila species show functional enhancer conservation and turnover during cis-regulatory evolution. Nature Genetics. 46(7). 685–692. 124 indexed citations
18.
Arnold, Cosmas D., Daniel Gerlach, Christoph Stelzer, et al.. (2013). Genome-Wide Quantitative Enhancer Activity Maps Identified by STARR-seq. Science. 339(6123). 1074–1077. 725 indexed citations breakdown →
19.
20.
Arnold, Cosmas D. & Ian Hodgson. (1991). Vectorette PCR: a novel approach to genomic walking.. Genome Research. 1(1). 39–42. 165 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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