Ewa Szczurek

3.5k total citations · 1 hit paper
38 papers, 863 citations indexed

About

Ewa Szczurek is a scholar working on Molecular Biology, Cancer Research and Artificial Intelligence. According to data from OpenAlex, Ewa Szczurek has authored 38 papers receiving a total of 863 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 14 papers in Cancer Research and 6 papers in Artificial Intelligence. Recurrent topics in Ewa Szczurek's work include Cancer Genomics and Diagnostics (12 papers), Bioinformatics and Genomic Networks (8 papers) and Single-cell and spatial transcriptomics (6 papers). Ewa Szczurek is often cited by papers focused on Cancer Genomics and Diagnostics (12 papers), Bioinformatics and Genomic Networks (8 papers) and Single-cell and spatial transcriptomics (6 papers). Ewa Szczurek collaborates with scholars based in Poland, Germany and Switzerland. Ewa Szczurek's co-authors include Niko Beerenwinkel, Marcin Możejko, Martin Vingron, Alicja Rączkowska, Jerzy Tiuryn, Thomas Sakoparnig, Dilafruz Juraeva, Eike Staub, Jörg Rahnenführer and Pejman Mohammadi and has published in prestigious journals such as The Lancet, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Ewa Szczurek

37 papers receiving 846 citations

Hit Papers

align trajectories sort by overperformance

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.

Discovering highly potent antimicrobial peptides with deep generative model HydrAMP

2023 98 citations Marcin Możejko, Marta Bauer et al. Nature Communications profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ewa Szczurek Poland	18	497	199	127	101	78	38	863
Harpreet Kaur India	24	1.0k 2.0×	260 1.3×	67 0.5×	80 0.8×	52 0.7×	118	1.6k
Boyang Zhao United States	12	366 0.7×	152 0.8×	26 0.2×	11 0.1×	65 0.8×	26	673
Harald Vöhringer Germany	4	724 1.5×	188 0.9×	223 1.8×	24 0.2×	96 1.2×	5	1.2k
Bryan D. Bryson United States	22	1.7k 3.4×	314 1.6×	52 0.4×	18 0.2×	136 1.7×	54	2.7k
Javier Rodríguez Colombia	16	323 0.6×	244 1.2×	46 0.4×	8 0.1×	32 0.4×	117	1.0k
Nicholas A. Cilfone United States	13	314 0.6×	32 0.2×	36 0.3×	14 0.1×	85 1.1×	17	1.1k
Yuhua Yao China	20	791 1.6×	107 0.5×	60 0.5×	12 0.1×	21 0.3×	65	982
Justin Bo‐Kai Hsu Taiwan	18	887 1.8×	349 1.8×	52 0.4×	41 0.4×	61 0.8×	28	1.4k
Mohammed El-Kebir United States	14	525 1.1×	386 1.9×	30 0.2×	10 0.1×	178 2.3×	48	869

Countries citing papers authored by Ewa Szczurek

Since Specialization

Citations

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

Fields of papers citing papers by Ewa Szczurek

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ewa Szczurek

This figure shows the co-authorship network connecting the top 25 collaborators of Ewa Szczurek. A scholar is included among the top collaborators of Ewa Szczurek 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 Ewa Szczurek. Ewa Szczurek 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:

20 of 20 papers shown

Koperski, Łukasz, Kim Thrane, Camilla Engblom, et al.. (2024). Integrative spatial and genomic analysis of tumor heterogeneity with Tumoroscope. Nature Communications. 15(1). 9343–9343. 6 indexed citations

Markowska, Magdalena, Magdalena A. Budzinska, Anna Coenen-Stass, et al.. (2023). Synthetic lethality prediction in DNA damage repair, chromatin remodeling and the cell cycle using multi-omics data from cell lines and patients.. Scientific Reports. 13(1). 7049–7049. 2 indexed citations

Możejko, Marcin, Marta Bauer, Damian Neubauer, et al.. (2023). Discovering highly potent antimicrobial peptides with deep generative model HydrAMP. Nature Communications. 14(1). 1453–1453. 98 indexed citations breakdown →

Miasojedow, Błażej, Dilafruz Juraeva, Johanna Mazur, et al.. (2022). CONET: copy number event tree model of evolutionary tumor history for single-cell data. Genome biology. 23(1). 17 indexed citations

Krueger, Tyll, Krzysztof Gogolewski, Marcin Bodych, et al.. (2022). Risk assessment of COVID-19 epidemic resurgence in relation to SARS-CoV-2 variants and vaccination passes. SHILAP Revista de lepidopterología. 2(1). 23–23. 37 indexed citations

Kuipers, Jack, et al.. (2022). SIEVE: joint inference of single-nucleotide variants and cell phylogeny from single-cell DNA sequencing data. Genome biology. 23(1). 248–248. 8 indexed citations

Gogolewski, Krzysztof, Błażej Miasojedow, Małgorzata Sadkowska-Todys, et al.. (2022). Data-driven case fatality rate estimation for the primary lineage of SARS-CoV-2 in Poland. Methods. 203. 584–593. 6 indexed citations

Rączkowska, Alicja, Marcin Nicoś, Magdalena A. Budzinska, et al.. (2022). Deep learning-based tumor microenvironment segmentation is predictive of tumor mutations and patient survival in non-small-cell lung cancer. BMC Cancer. 22(1). 1001–1001. 16 indexed citations

Schmich, Fabian, et al.. (2021). Learning epistatic gene interactions from perturbation screens. PLoS ONE. 16(7). e0254491–e0254491. 2 indexed citations

10.

Kiełbasa, Szymon M., Ramin Monajemi, Davy Cats, et al.. (2021). CACTUS: integrating clonal architecture with genomic clustering and transcriptome profiling of single tumor cells. Genome Medicine. 13(1). 45–45. 6 indexed citations

11.

Juraeva, Dilafruz, et al.. (2020). Feature selection strategies for drug sensitivity prediction. Scientific Reports. 10(1). 9377–9377. 37 indexed citations

12.

Rączkowska, Alicja, et al.. (2019). ARA: accurate, reliable and active histopathological image classification framework with Bayesian deep learning. Scientific Reports. 9(1). 14347–14347. 79 indexed citations

13.

Szczurek, Ewa & Niko Beerenwinkel. (2016). Linear effects models of signaling pathways from combinatorial perturbation data. Bioinformatics. 32(12). i297–i305. 3 indexed citations

14.

Schmich, Fabian, Ewa Szczurek, Saskia Kreibich, et al.. (2015). gespeR: a statistical model for deconvoluting off-target-confounded RNA interference screens. Genome biology. 16(1). 220–220. 28 indexed citations

15.

Szczurek, Ewa & Niko Beerenwinkel. (2014). Modeling Mutual Exclusivity of Cancer Mutations. Lecture notes in computer science. 10(3). 307–308. 55 indexed citations

16.

Szczurek, Ewa & Niko Beerenwinkel. (2014). Modeling Mutual Exclusivity of Cancer Mutations. PLoS Computational Biology. 10(3). e1003503–e1003503. 59 indexed citations

17.

Jankowski, Aleksander, Ewa Szczurek, Ralf Jauch, Jerzy Tiuryn, & Shyam Prabhakar. (2013). Comprehensive prediction in 78 human cell lines reveals rigidity and compactness of transcription factor dimers. Genome Research. 23(8). 1307–1318. 29 indexed citations

18.

Biecek, Przemysław, Ewa Szczurek, Martin Vingron, & Jerzy Tiuryn. (2012). The R Package bgmm: Mixture Modeling with Uncertain Knowledge. SHILAP Revista de lepidopterología. 3 indexed citations

19.

Szczurek, Ewa, Przemysław Biecek, Jerzy Tiuryn, & Martin Vingron. (2010). Introducing Knowledge into Differential Expression Analysis. Journal of Computational Biology. 17(8). 953–967. 7 indexed citations

20.

Grynberg, Marcin, Zhanwen Li, Ewa Szczurek, & Adam Godzik. (2007). Putative type IV secretion genes in Bacillus anthracis. Trends in Microbiology. 15(5). 191–195. 13 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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