Michał Komorowski

1.2k citations
25 papers · 762 indexed · h-index 15
Topics
Gene Regulatory Network Analysis (17 papers)Computational Drug Discovery Methods (4 papers)Microbial Metabolic Engineering and Bioproduction (4 papers)

In The Last Decade

Michał Komorowski

24 papers receiving 747 citations

Peers

Michał Komorowski
Comparison fields: 5 of 116
  • Molecular Biology 538
  • Genetics 126
  • Immunology 70
  • Biophysics 67
  • Computational Theory and Mathematics 65
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Julie Bachmann Germany
Nicole Radde Germany
Nicolás Rodríguez United Kingdom
Daniel Kaschek Germany
Thomas Thorne United Kingdom
Vijayalakshmi Chelliah United Kingdom
Fabian Fröhlich Germany
Gabriele Lillacci United States
Chen‐An Tsai Taiwan
Sabine Hug Germany
Michał Komorowski relative to Julie Bachmann Germany Julie Bachmann's profile →
Citations per field
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Citations per year

Countries citing papers authored by Michał Komorowski

Since Specialization
Citations

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

Fields of papers citing papers by Michał Komorowski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michał Komorowski

This figure shows the co-authorship network connecting the top 25 collaborators of Michał Komorowski. A scholar is included among the top collaborators of Michał Komorowski 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 Michał Komorowski. Michał Komorowski 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 16
4 35
5 11
6 43
7 38
8 16
9 20
10 31
11 12
12 52
13 26
14 3
15 121
16 7
17 135
18 19
19 74
20 23

About Michał Komorowski

Michał Komorowski is a scholar working on Biophysics, Molecular Biology and Computational Theory and Mathematics, having authored 25 papers that have together received 762 indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (17 papers), Computational Drug Discovery Methods (4 papers) and Microbial Metabolic Engineering and Bioproduction (4 papers). The work is most often cited by research in Biophysics (67 citations), Molecular Biology (538 citations) and Modeling and Simulation (36 citations). Michał Komorowski has collaborated with scholars based in Poland, United Kingdom and Germany. Frequent co-authors include Michael P. H. Stumpf, D.A.J. Rand, Sarah Filippi, María José Costa, Juliane Liepe, Bärbel Finkenstädt, Claire V. Harper, Jacek Miȩkisz, Anna Dittrich and Fred Schaper. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and Bioinformatics.

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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