Tomasz Uchański

2.7k total citations · 1 hit paper
15 papers, 1.0k citations indexed

About

Tomasz Uchański is a scholar working on Molecular Biology, Immunology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Tomasz Uchański has authored 15 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 6 papers in Immunology and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Tomasz Uchański's work include Monoclonal and Polyclonal Antibodies Research (5 papers), Glycosylation and Glycoproteins Research (4 papers) and Receptor Mechanisms and Signaling (4 papers). Tomasz Uchański is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (5 papers), Glycosylation and Glycoproteins Research (4 papers) and Receptor Mechanisms and Signaling (4 papers). Tomasz Uchański collaborates with scholars based in Belgium, United States and Luxembourg. Tomasz Uchański's co-authors include Jan Steyaert, Els Pardon, Simonas Masiulis, A.R. Aricescu, Duncan Laverty, Keith W. Miller, Jasenko Zivanov, Tomas Malinauskas, Rooma Desai and Abhay Kotecha and has published in prestigious journals such as Nature, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Tomasz Uchański

14 papers receiving 995 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

GABAA receptor signalling mechanisms revealed by structural pharmacology

2018 399 citations Simonas Masiulis, Rooma Desai et al. Nature profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Tomasz Uchański Belgium	11	733	380	162	84	78	15	1.0k
Antoine Koehl United States	12	1.3k 1.7×	655 1.7×	138 0.9×	34 0.4×	53 0.7×	15	1.5k
Javier García‐Nafría United Kingdom	18	1.4k 1.9×	666 1.8×	179 1.1×	38 0.5×	43 0.6×	32	1.7k
Jeffrey Tarrasch United States	10	1.6k 2.2×	769 2.0×	214 1.3×	123 1.5×	129 1.7×	11	2.0k
Stephen G. Brohawn United States	21	1.8k 2.4×	603 1.6×	85 0.5×	61 0.7×	32 0.4×	36	2.5k
Alpay B. Seven United States	20	1.4k 1.8×	697 1.8×	140 0.9×	41 0.5×	23 0.3×	24	1.7k
Shaoda He United Kingdom	8	1.3k 1.8×	250 0.7×	68 0.4×	47 0.6×	42 0.5×	10	2.0k
Dimple Karia United Kingdom	12	614 0.8×	292 0.8×	30 0.2×	131 1.6×	26 0.3×	17	1.0k
Simonas Masiulis United Kingdom	9	799 1.1×	560 1.5×	58 0.4×	33 0.4×	11 0.1×	14	1.1k
Rémy Sounier France	15	1.0k 1.4×	308 0.8×	91 0.6×	24 0.3×	43 0.6×	27	1.2k
Moran Shalev-Benami Israel	11	607 0.8×	259 0.7×	47 0.3×	28 0.3×	25 0.3×	14	834

Countries citing papers authored by Tomasz Uchański

Since Specialization

Citations

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

Fields of papers citing papers by Tomasz Uchański

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tomasz Uchański

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

All Works

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15 of 15 papers shown

Fischer, Baptiste, Tomasz Uchański, Alexander N. Volkov, et al.. (2024). Allosteric nanobodies to study the interactions between SOS1 and RAS. Nature Communications. 15(1). 6214–6214. 2 indexed citations

Uchański, Tomasz, et al.. (2024). Rapid small-scale nanobody-assisted purification of ryanodine receptors for cryo-EM. Journal of Biological Chemistry. 300(10). 107734–107734.

Zarkadas, Eleftherios, Eva Pebay‐Peyroula, Guy Schoehn, et al.. (2022). Conformational transitions and ligand-binding to a muscle-type nicotinic acetylcholine receptor. Neuron. 110(8). 1358–1370.e5. 50 indexed citations

Meyrath, Max, Tomasz Uchański, Bernard Rogister, et al.. (2022). Nanoluciferase-based methods to monitor activation, modulation and trafficking of atypical chemokine receptors. Methods in cell biology. 169. 279–294. 12 indexed citations

Meyrath, Max, et al.. (2022). Nanoluciferase-based complementation assay for systematic profiling of GPCR–GRK interactions. Methods in cell biology. 169. 309–321. 6 indexed citations

Meyrath, Max, Tomasz Uchański, Toon Laeremans, et al.. (2022). The Extended N-Terminal Domain Confers Atypical Chemokine Receptor Properties to CXCR3-B. Frontiers in Immunology. 13. 868579–868579. 13 indexed citations

Uchański, Tomasz, Simonas Masiulis, Baptiste Fischer, et al.. (2021). Megabodies expand the nanobody toolkit for protein structure determination by single-particle cryo-EM. Nature Methods. 18(1). 60–68. 86 indexed citations

Chevigné, Andy, Bassam Janji, Max Meyrath, et al.. (2021). CXCL10 Is an Agonist of the CC Family Chemokine Scavenger Receptor ACKR2/D6. Cancers. 13(5). 1054–1054. 33 indexed citations

Uchański, Tomasz, Els Pardon, & Jan Steyaert. (2020). Nanobodies to study protein conformational states. Current Opinion in Structural Biology. 60. 117–123. 66 indexed citations

10.

Meyrath, Max, et al.. (2020). Systematic reassessment of chemokine-receptor pairings confirms CCL20 but not CXCL13 and extends the spectrum of ACKR4 agonists to CCL22. Journal of Leukocyte Biology. 109(2). 373–376. 21 indexed citations

11.

Uchański, Tomasz, Thomas Zögg, Jie Yin, et al.. (2019). An improved yeast surface display platform for the screening of nanobody immune libraries. Scientific Reports. 9(1). 382–382. 79 indexed citations

12.

Fărcăşanu, M, Tomasz Uchański, L.J. Bailey, et al.. (2019). Rapid Discovery and Characterization of Synthetic Neutralizing Antibodies against Anthrax Edema Toxin. Biochemistry. 58(27). 2996–3004. 5 indexed citations

13.

Masiulis, Simonas, Rooma Desai, Tomasz Uchański, et al.. (2018). GABAA receptor signalling mechanisms revealed by structural pharmacology. Nature. 565(7740). 454–459. 399 indexed citations breakdown →

14.

Laverty, Duncan, Rooma Desai, Tomasz Uchański, et al.. (2018). Cryo-EM structure of the human α1β3γ2 GABAA receptor in a lipid bilayer. Nature. 565(7740). 516–520. 223 indexed citations

15.

Uchański, Tomasz, et al.. (2015). A new expression vector facilitating production and functional analysis of scFv antibody fragments selected from Tomlinson I + J phagemid libraries. Immunology Letters. 167(2). 95–102. 17 indexed citations

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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