Jakub Galgonek

43 total papers · 650 total citations
21 papers, 318 citations indexed

About

Jakub Galgonek is a scholar working on Molecular Biology, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Jakub Galgonek has authored 21 papers receiving a total of 318 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 7 papers in Computational Theory and Mathematics and 4 papers in Artificial Intelligence. Recurrent topics in Jakub Galgonek's work include Protein Structure and Dynamics (9 papers), Computational Drug Discovery Methods (7 papers) and Machine Learning in Bioinformatics (5 papers). Jakub Galgonek is often cited by papers focused on Protein Structure and Dynamics (9 papers), Computational Drug Discovery Methods (7 papers) and Machine Learning in Bioinformatics (5 papers). Jakub Galgonek collaborates with scholars based in Czechia, Switzerland and Canada. Jakub Galgonek's co-authors include Jiřı́ Vondrášek, Jiří Vymětal, Jonathan Bisson, Arnaud Gaudry, Ralf Stephan, Guido F. Pauli, Adriano Rutz, Daniel Mietchen, Roderic Page and Maria Sorokina and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and The Journal of Physical Chemistry B.

In The Last Decade

Jakub Galgonek

20 papers receiving 311 citations

Hit Papers

The LOTUS initiative for ... 2022 2026 2023 2024 2022 50 100 150

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Jakub Galgonek 225 75 56 34 30 21 318
Natália Aniceto 173 0.8× 147 2.0× 33 0.6× 14 0.4× 44 1.5× 19 360
Antje Wolf 190 0.8× 81 1.1× 35 0.6× 51 1.5× 23 0.8× 18 336
Peter Merseburger 224 1.0× 150 2.0× 94 1.7× 24 0.7× 30 1.0× 11 363
Patrick Penner 157 0.7× 136 1.8× 39 0.7× 8 0.2× 42 1.4× 20 274
Marie-Claude Blatter 228 1.0× 59 0.8× 21 0.4× 16 0.5× 23 0.8× 10 300
Alban Arrault 170 0.8× 131 1.7× 51 0.9× 15 0.4× 32 1.1× 12 343
Bhanuranjan Das 136 0.6× 122 1.6× 34 0.6× 8 0.2× 36 1.2× 20 316
Mingjie Gao 189 0.8× 74 1.0× 79 1.4× 39 1.1× 8 0.3× 19 311
Kelsey L. Alexander 132 0.6× 30 0.4× 82 1.5× 21 0.6× 10 0.3× 9 240
Daniel Korn 159 0.7× 196 2.6× 25 0.4× 19 0.6× 27 0.9× 25 364

Countries citing papers authored by Jakub Galgonek

Since Specialization
Citations

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

Fields of papers citing papers by Jakub Galgonek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jakub Galgonek

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

All Works

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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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