Ewa Szczurek

3.5k citations
38 papers · 863 indexed · 1 hit paper · h-index 18
Topics
Cancer Genomics and Diagnostics (12 papers)Bioinformatics and Genomic Networks (8 papers)Single-cell and spatial transcriptomics (6 papers)
Journals
The LancetNature CommunicationsSHILAP Revista de lepidopterología
Partner nations
PolandGermanySwitzerland

In The Last Decade

Ewa Szczurek

37 papers receiving 846 citations

Hit Papers

Discovering highly potent antimicrobial peptides with dee...20232026202420252023255075

Peers

Ewa Szczurek
Comparison fields: 5 of 116
  • Molecular Biology 497
  • Cancer Research 199
  • Artificial Intelligence 127
  • Microbiology 101
  • Genetics 78
Replace Harpreet Kaur with:
Harpreet Kaur India
Bryan D. Bryson United States
Boyang Zhao United States
Haihe Wang China
Hailin Hu China
Vladimir Gligorijević United States
Nadav Rappoport Israel
Angela M. Jarrett United States
Harald Vöhringer Germany
Ewa Szczurek relative to Harpreet Kaur India Harpreet Kaur's profile →
Citations per field
00.5×1.5×1.9×
Harpreet Kaur · 1×
Citations per year

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

20 of 20 papers shown
#WorkIndexed citations
1 1
2 6
3 0
4 2
5
Discovering highly potent antimicrobial peptides with deep generative model HydrAMPbreakdown →
98
6 17
7 37
8 6
9 16
10 2
11 73
12 37
13 79
14 28
15 59
16 29
17
The R Package bgmm: Mixture Modeling with Uncertain Knowledge
3
18 7
19 6
20 13

About Ewa Szczurek

Ewa Szczurek is a scholar working on Modeling and Simulation, Cancer Research and Microbiology, having authored 38 papers that have together received 863 indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (12 papers), Bioinformatics and Genomic Networks (8 papers) and Single-cell and spatial transcriptomics (6 papers). The work is most often cited by research in Microbiology (101 citations), Modeling and Simulation (70 citations) and Cancer Research (199 citations). Ewa Szczurek has collaborated with scholars based in Poland, Germany and Switzerland. Frequent co-authors include Niko Beerenwinkel, Marcin Możejko, Martin Vingron, Alicja Rączkowska, Jerzy Tiuryn, Eike Staub, Thomas Sakoparnig, Dilafruz Juraeva, Jörg Rahnenführer and Pejman Mohammadi. Their work appears in journals such as The Lancet, Nature Communications and SHILAP Revista de lepidopterología.

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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