Artur Yakimovich

1.1k total citations
38 papers, 653 citations indexed

About

Artur Yakimovich is a scholar working on Genetics, Biophysics and Epidemiology. According to data from OpenAlex, Artur Yakimovich has authored 38 papers receiving a total of 653 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Genetics, 14 papers in Biophysics and 11 papers in Epidemiology. Recurrent topics in Artur Yakimovich's work include Virus-based gene therapy research (16 papers), Cell Image Analysis Techniques (10 papers) and Herpesvirus Infections and Treatments (8 papers). Artur Yakimovich is often cited by papers focused on Virus-based gene therapy research (16 papers), Cell Image Analysis Techniques (10 papers) and Herpesvirus Infections and Treatments (8 papers). Artur Yakimovich collaborates with scholars based in United Kingdom, Switzerland and Germany. Artur Yakimovich's co-authors include Urs F. Greber, Christoph J. Burckhardt, I-Hsuan Wang, Jason Mercer, Vardan Andriasyan, Fanny Georgi, Eva‐Maria Frickel, Barbara Clough, Ivo F. Sbalzarini and Daniel J. Müller and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Journal of Cell Biology and PLoS ONE.

In The Last Decade

Artur Yakimovich

36 papers receiving 638 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Artur Yakimovich United Kingdom 15 265 237 176 141 104 38 653
I-Hsuan Wang United States 10 276 1.0× 246 1.0× 183 1.0× 127 0.9× 41 0.4× 13 619
Vardan Andriasyan Switzerland 10 161 0.6× 171 0.7× 95 0.5× 90 0.6× 53 0.5× 20 377
Renato Mancini Astray Brazil 15 324 1.2× 167 0.7× 108 0.6× 110 0.8× 31 0.3× 50 616
Jens B. Bosse Germany 18 267 1.0× 140 0.6× 470 2.7× 62 0.4× 32 0.3× 39 774
William J. Godinez Germany 17 466 1.8× 115 0.5× 147 0.8× 67 0.5× 338 3.3× 35 1.0k
David K. Cureton United States 12 423 1.6× 245 1.0× 261 1.5× 319 2.3× 25 0.2× 12 1.0k
Simon Delagrave United States 17 426 1.6× 166 0.7× 315 1.8× 281 2.0× 135 1.3× 31 1.1k
Nathalie Aulner France 16 783 3.0× 117 0.5× 184 1.0× 65 0.5× 75 0.7× 29 1.4k
Martin Gaudier United Kingdom 7 554 2.1× 288 1.2× 182 1.0× 65 0.5× 44 0.4× 9 872
Grace Hui Ting Yeo United States 4 429 1.6× 179 0.8× 162 0.9× 240 1.7× 20 0.2× 4 942

Countries citing papers authored by Artur Yakimovich

Since Specialization
Citations

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

Fields of papers citing papers by Artur Yakimovich

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Artur Yakimovich

This figure shows the co-authorship network connecting the top 25 collaborators of Artur Yakimovich. A scholar is included among the top collaborators of Artur Yakimovich 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 Artur Yakimovich. Artur Yakimovich 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.
Yakimovich, Artur, et al.. (2025). Artificial Intelligence Methods in Infection Biology Research. Methods in molecular biology. 2890. 291–333. 1 indexed citations
2.
Urbanski, A, et al.. (2025). A digital photography dataset for Vaccinia Virus plaque quantification using Deep Learning. Scientific Data. 12(1). 719–719.
3.
Yakimovich, Artur, János Kriston-Vizi, Moona Huttunen, et al.. (2024). Vaccinia virus subverts xenophagy through phosphorylation and nuclear targeting of p62. The Journal of Cell Biology. 223(6). 3 indexed citations
4.
Galimov, Evgeniy R. & Artur Yakimovich. (2022). A tandem segmentation-classification approach for the localization of morphological predictors of C. elegans lifespan and motility. Aging. 14(4). 1665–1677. 2 indexed citations
5.
Georgi, Fanny, Vardan Andriasyan, Fabien Kuttler, et al.. (2022). High-content, arrayed compound screens with rhinovirus, influenza A virus and herpes simplex virus infections. Scientific Data. 9(1). 610–610. 4 indexed citations
6.
Huttunen, Moona, Robert J. Evans, Artur Yakimovich, et al.. (2021). Vaccinia virus hijacks ESCRT-mediated multivesicular body formation for virus egress. Life Science Alliance. 4(8). e202000910–e202000910. 21 indexed citations
7.
Andriasyan, Vardan, et al.. (2021). Microscopy deep learning predicts virus infections and reveals mechanics of lytic-infected cells. iScience. 24(6). 102543–102543. 23 indexed citations
8.
Yakimovich, Artur, et al.. (2021). Labels in a haystack: Approaches beyond supervised learning in biomedical applications. Patterns. 2(12). 100383–100383. 16 indexed citations
9.
Yakimovich, Artur. (2021). Machine Learning and Artificial Intelligence for the Prediction of Host–Pathogen Interactions: A Viral Case. Infection and Drug Resistance. Volume 14. 3319–3326. 8 indexed citations
10.
Georgi, Fanny, Fabien Kuttler, Vardan Andriasyan, et al.. (2020). A high-content image-based drug screen of clinical compounds against cell transmission of adenovirus. Scientific Data. 7(1). 265–265. 15 indexed citations
11.
Georgi, Fanny, Vardan Andriasyan, Silvio Hemmi, et al.. (2020). The FDA-Approved Drug Nelfinavir Inhibits Lytic Cell-Free but Not Cell-Associated Nonlytic Transmission of Human Adenovirus. Antimicrobial Agents and Chemotherapy. 64(9). 23 indexed citations
12.
Fisch, Daniel, Artur Yakimovich, Barbara Clough, et al.. (2019). Defining host–pathogen interactions employing an artificial intelligence workflow. eLife. 8. 61 indexed citations
13.
Fisch, Daniel, Artur Yakimovich, Barbara Clough, Jason Mercer, & Eva‐Maria Frickel. (2019). Image-Based Quantitation of Host Cell–Toxoplasma gondii Interplay Using HRMAn: A Host Response to Microbe Analysis Pipeline. Methods in molecular biology. 2071. 411–433. 9 indexed citations
14.
Andriasyan, Vardan, et al.. (2018). Concepts in Light Microscopy of Viruses. Viruses. 10(4). 202–202. 37 indexed citations
15.
Wang, I-Hsuan, Christoph J. Burckhardt, Artur Yakimovich, & Urs F. Greber. (2018). Imaging, Tracking and Computational Analyses of Virus Entry and Egress with the Cytoskeleton. Viruses. 10(4). 166–166. 79 indexed citations
16.
Yakimovich, Artur, et al.. (2018). Label-Free Digital Holo-tomographic Microscopy Reveals Virus-Induced Cytopathic Effects in Live Cells. mSphere. 3(6). 20 indexed citations
17.
Yakimovich, Artur, Samuel Kilcher, Glennys V. Reynoso, et al.. (2018). Vaccinia virus hijacks EGFR signalling to enhance virus spread through rapid and directed infected cell motility. Nature Microbiology. 4(2). 216–225. 73 indexed citations
18.
Wang, I-Hsuan, et al.. (2017). The nuclear export factor CRM1 controls juxta-nuclear microtubule-dependent virus transport. Journal of Cell Science. 130(13). 2185–2195. 33 indexed citations
19.
20.
Prasad, Vibhu, Maarit Suomalainen, Artur Yakimovich, et al.. (2014). Chemical Induction of Unfolded Protein Response Enhances Cancer Cell Killing through Lytic Virus Infection. Journal of Virology. 88(22). 13086–13098. 24 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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