Tomasz Klucznik

1.7k citations
15 papers · 1.1k indexed · 1 hit paper · h-index 10
Topics
Machine Learning in Materials Science (5 papers)Computational Drug Discovery Methods (5 papers)Microbial Natural Products and Biosynthesis (4 papers)

In The Last Decade

Tomasz Klucznik

15 papers receiving 1.1k citations

Hit Papers

Computer‐Assisted Synthetic Planning: The End of the Begi...20162026201920222016100200300400

Peers

Tomasz Klucznik
Comparison fields: 5 of 87
  • Materials Chemistry 624
  • Computational Theory and Mathematics 574
  • Molecular Biology 454
  • Biomedical Engineering 239
  • Organic Chemistry 144
Replace Piotr Dittwald with:
Piotr Dittwald Poland
Karol Molga Poland
Sara Szymkuć Poland
Timur Madzhidov Russia
AkshatKumar Nigam Canada
Wiktor Beker Poland
Ruud van Deursen Switzerland
Barbara Mikulak-Klucznik South Korea
Lars Ruddigkeit Switzerland
Robert W. Hicklin United States
Tomasz Klucznik relative to Piotr Dittwald Poland Piotr Dittwald's profile →
Citations per field
00.5×1.5×
Piotr Dittwald · 1×
Citations per year

Countries citing papers authored by Tomasz Klucznik

Since Specialization
Citations

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

Fields of papers citing papers by Tomasz Klucznik

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tomasz Klucznik

This figure shows the co-authorship network connecting the top 25 collaborators of Tomasz Klucznik. A scholar is included among the top collaborators of Tomasz Klucznik 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 Tomasz Klucznik. Tomasz Klucznik is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
#WorkIndexed citations
1 1
2 8
3 6
4 9
5 6
6 18
7 187
8 23
9 69
10 65
11 246
12
Computer‐Assisted Synthetic Planning: The End of the Beginningbreakdown →
406
13 34
14 16
15 11

About Tomasz Klucznik

Tomasz Klucznik is a scholar working on Computational Theory and Mathematics, Pharmacology and Physical and Theoretical Chemistry, having authored 15 papers that have together received 1.1k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (5 papers), Computational Drug Discovery Methods (5 papers) and Microbial Natural Products and Biosynthesis (4 papers). The work is most often cited by research in Computational Theory and Mathematics (574 citations), Materials Chemistry (624 citations) and Catalysis (50 citations). Tomasz Klucznik has collaborated with scholars based in South Korea, Poland and United States. Frequent co-authors include Bartosz A. Grzybowski, Sara Szymkuć, Karol Molga, Ewa Gajewska, Piotr Dittwald, Michał Startek, Michał D. Bajczyk, Barbara Mikulak-Klucznik, Milan Mrksich and Wiktor Beker. Their work appears in journals such as Nature, Journal of the American Chemical Society and Advanced Materials.

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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