Nicolas Mathis

588 total citations · 2 hit papers
12 papers, 362 citations indexed

About

Nicolas Mathis is a scholar working on Molecular Biology, Genetics and Hematology. According to data from OpenAlex, Nicolas Mathis has authored 12 papers receiving a total of 362 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 4 papers in Genetics and 2 papers in Hematology. Recurrent topics in Nicolas Mathis's work include CRISPR and Genetic Engineering (9 papers), RNA and protein synthesis mechanisms (5 papers) and RNA regulation and disease (4 papers). Nicolas Mathis is often cited by papers focused on CRISPR and Genetic Engineering (9 papers), RNA and protein synthesis mechanisms (5 papers) and RNA regulation and disease (4 papers). Nicolas Mathis collaborates with scholars based in Switzerland, United States and Germany. Nicolas Mathis's co-authors include Gerald Schwank, Lukas Schmidheini, Kim Fabiano Marquart, Tanja Rothgangl, Lucas Kissling, Desirée Böck, Ahmed Allam, Michael Krauthammer, Lukas Villiger and Zsolt Balázs and has published in prestigious journals such as Nature Communications, Nature Biotechnology and Molecular Cell.

In The Last Decade

Nicolas Mathis

11 papers receiving 360 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

In vivo prime editing of a metabolic liver disease in mice

2022 130 citations Desirée Böck, Tanja Rothgangl et al. Science Translational Medicine profile →
Predicting prime editing efficiency and product purity by deep learning

2023 84 citations Nicolas Mathis, Ahmed Allam et al. Nature Biotechnology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Nicolas Mathis Switzerland	9	321	117	28	25	24	12	362
Tanja Rothgangl Switzerland	8	281 0.9×	111 0.9×	21 0.8×	22 0.9×	17 0.7×	9	303
Grégoire Cullot France	5	389 1.2×	108 0.9×	40 1.4×	31 1.2×	40 1.7×	10	418
Kim Fabiano Marquart Switzerland	10	315 1.0×	95 0.8×	25 0.9×	18 0.7×	19 0.8×	13	336
Sung-Ah Hong South Korea	9	266 0.8×	97 0.8×	21 0.8×	17 0.7×	18 0.8×	11	313
David J Menn United States	4	373 1.2×	73 0.6×	22 0.8×	11 0.4×	14 0.6×	6	407
Nada Kubikova United Kingdom	6	399 1.2×	100 0.9×	16 0.6×	15 0.6×	45 1.9×	10	464
Congting Guo China	3	245 0.8×	55 0.5×	35 1.3×	25 1.0×	29 1.2×	5	306
Yeonsoo Yoon United States	7	367 1.1×	123 1.1×	21 0.8×	11 0.4×	38 1.6×	9	396
Sneha Suresh United States	4	369 1.1×	71 0.6×	18 0.6×	14 0.6×	42 1.8×	4	387
Kankan Wang China	10	398 1.2×	224 1.9×	34 1.2×	31 1.2×	10 0.4×	19	468

Countries citing papers authored by Nicolas Mathis

Since Specialization

Citations

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

Fields of papers citing papers by Nicolas Mathis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nicolas Mathis

This figure shows the co-authorship network connecting the top 25 collaborators of Nicolas Mathis. A scholar is included among the top collaborators of Nicolas Mathis 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 Nicolas Mathis. Nicolas Mathis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

1.

Mathis, Nicolas, Kim Fabiano Marquart, Ahmed Allam, Michael Krauthammer, & Gerald Schwank. (2025). Systematic pegRNA design with PRIDICT2.0 and ePRIDICT for efficient prime editing. Nature Protocols. 1 indexed citations

2.

Kissling, Lucas, Sharan Janjuha, Nicolas Mathis, et al.. (2025). Predicting adenine base editing efficiencies in different cellular contexts by deep learning. Genome biology. 26(1). 115–115.

3.

Marquart, Kim Fabiano, Nicolas Mathis, Lucas Kissling, et al.. (2024). Effective genome editing with an enhanced ISDra2 TnpB system and deep learning-predicted ωRNAs. Nature Methods. 21(11). 2084–2093. 8 indexed citations

4.

Mathis, Nicolas, Ahmed Allam, András Tálas, et al.. (2024). Machine learning prediction of prime editing efficiency across diverse chromatin contexts. Nature Biotechnology. 43(5). 712–719. 27 indexed citations

5.

Böck, Desirée, Nicolas Mathis, Tanja Rothgangl, et al.. (2024). Enhancing prime editor activity by directed protein evolution in yeast. Nature Communications. 15(1). 2092–2092. 12 indexed citations

6.

Schmidheini, Lukas, Nicolas Mathis, Kim Fabiano Marquart, et al.. (2023). Continuous directed evolution of a compact CjCas9 variant with broad PAM compatibility. Nature Chemical Biology. 20(3). 333–343. 24 indexed citations

7.

Mathis, Nicolas, Ahmed Allam, Lucas Kissling, et al.. (2023). Predicting prime editing efficiency and product purity by deep learning. Nature Biotechnology. 41(8). 1151–1159. 84 indexed citations breakdown →

8.

Böck, Desirée, Tanja Rothgangl, Lukas Villiger, et al.. (2022). In vivo prime editing of a metabolic liver disease in mice. Science Translational Medicine. 14(636). eabl9238–eabl9238. 130 indexed citations breakdown →

9.

Jacobs, Kurt, Jana Krietsch, Daniel González‐Acosta, et al.. (2022). Stress-triggered hematopoietic stem cell proliferation relies on PrimPol-mediated repriming. Molecular Cell. 82(21). 4176–4188.e8. 16 indexed citations

10.

Villiger, Lukas, Lukas Schmidheini, Nicolas Mathis, et al.. (2021). Replacing the SpCas9 HNH domain by deaminases generates compact base editors with an alternative targeting scope. Molecular Therapy — Nucleic Acids. 26. 502–510. 12 indexed citations

11.

Cangkrama, Michael, Mateusz S. Wietecha, Nicolas Mathis, et al.. (2020). A paracrine activin A–mDia2 axis promotes squamous carcinogenesis via fibroblast reprogramming. EMBO Molecular Medicine. 12(4). 43 indexed citations

12.

Gerth‐Kahlert, Christina, Mathias Abegg, Deborah Bartholdi, et al.. (2017). Characterization of two novel intronic OPA1 mutations resulting in aberrant pre-mRNA splicing. BMC Medical Genetics. 18(1). 22–22. 5 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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