Stefan Przyborski

9.7k citations
133 papers · 6.6k indexed · 1 hit paper · h-index 50
Topics
Pluripotent Stem Cells Research (37 papers)3D Printing in Biomedical Research (23 papers)CRISPR and Genetic Engineering (22 papers)

In The Last Decade

Stefan Przyborski

129 papers receiving 6.5k citations

Hit Papers

Advances in 3D cell culture technologies enabling tissue‐...20142026201820222014100200300400

Peers

Stefan Przyborski
Comparison fields: 5 of 152
  • Molecular Biology 3.5k
  • Biomedical Engineering 1.5k
  • Cellular and Molecular Neuroscience 986
  • Surgery 839
  • Developmental Neuroscience 736
Replace Jianwu Dai with:
Jianwu Dai China
Renjie Chai China
Cecilia Sahlgren Finland
Yannan Zhao China
Sean P. Palecek United States
Yoshihisa Koyama Japan
Zhifeng Xiao China
Hang Lin United States
Bengt R. Johansson Sweden
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Citations per field
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Citations per year

Countries citing papers authored by Stefan Przyborski

Since Specialization
Citations

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

Fields of papers citing papers by Stefan Przyborski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stefan Przyborski

This figure shows the co-authorship network connecting the top 25 collaborators of Stefan Przyborski. A scholar is included among the top collaborators of Stefan Przyborski 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 Stefan Przyborski. Stefan Przyborski 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 0
3 1
4 8
5 0
6 10
7 9
8 18
9 13
10 14
11 19
12 9
13 11
14 115
15 11
16 70
17 21
18 28
19 64
20 16

About Stefan Przyborski

Stefan Przyborski is a scholar working on Developmental Neuroscience, Dermatology and Cell Biology, having authored 133 papers that have together received 6.6k indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (37 papers), 3D Printing in Biomedical Research (23 papers) and CRISPR and Genetic Engineering (22 papers). The work is most often cited by research in Developmental Neuroscience (736 citations), Cellular and Molecular Neuroscience (986 citations) and Molecular Biology (3.5k citations). Stefan Przyborski has collaborated with scholars based in United Kingdom, United States and Spain. Frequent co-authors include Neil R. Cameron, Eleanor Knight, Miodrag Stojković, Majlinda Lako, Maria Bokhari, Lyle Armstrong, Susan L. Ackerman, Daniel J. Maltman, Andrew Wood and Petra Stojković. Their work appears in journals such as Nature, Journal of the American Chemical Society and Journal of Neuroscience.

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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