Ágnes Tóth-Petróczy

2.2k total citations
34 papers, 1.4k citations indexed

About

Ágnes Tóth-Petróczy is a scholar working on Molecular Biology, Genetics and Materials Chemistry. According to data from OpenAlex, Ágnes Tóth-Petróczy has authored 34 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Molecular Biology, 7 papers in Genetics and 5 papers in Materials Chemistry. Recurrent topics in Ágnes Tóth-Petróczy's work include RNA and protein synthesis mechanisms (19 papers), Genomics and Phylogenetic Studies (10 papers) and Protein Structure and Dynamics (8 papers). Ágnes Tóth-Petróczy is often cited by papers focused on RNA and protein synthesis mechanisms (19 papers), Genomics and Phylogenetic Studies (10 papers) and Protein Structure and Dynamics (8 papers). Ágnes Tóth-Petróczy collaborates with scholars based in Germany, Israel and United States. Ágnes Tóth-Petróczy's co-authors include Dan S. Tawfik, Mónika Fuxreiter, Eynat Dellus-Gur, Mikael Elias, Yaakov Levy, István Simon, Vladimir N. Uversky, Thomas A. Hopf, John Ingraham and Chris Sander and has published in prestigious journals such as Cell, Chemical Reviews and Proceedings of the National Academy of Sciences.

In The Last Decade

Ágnes Tóth-Petróczy

31 papers receiving 1.3k citations

Peers

Ágnes Tóth-Petróczy

GENET

Todd Holyoak United States

Peter Haebel Germany

Benoît H. Dessailly United Kingdom

Coos Baakman Netherlands

Giulia Calloni Germany

Jean Marc Kwasigroch Belgium

John A. Buglino United States

David F. Lowry United States

Kimberly A. Reynolds United States

Suganthi Balasubramanian United States

Todd Holyoak United States

Ágnes Tóth-Petróczy

935 ×0.8

308 ×1.1

216 ×1.0

GENET

137 ×1.6

47 ×0.8

Citations per year, relative to Ágnes Tóth-Petróczy Ágnes Tóth-Petróczy (= 1×) peers Todd Holyoak

Countries citing papers authored by Ágnes Tóth-Petróczy

Since Specialization

Citations

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

Fields of papers citing papers by Ágnes Tóth-Petróczy

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ágnes Tóth-Petróczy. 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 Ágnes Tóth-Petróczy. The network helps show where Ágnes Tóth-Petróczy may publish in the future.

Co-authorship network of co-authors of Ágnes Tóth-Petróczy

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

All Works

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20 of 20 papers shown

Lenz, Swantje, et al.. (2025). Deep learning tools predict variants in disordered regions with lower sensitivity. BMC Genomics. 26(1). 367–367. 1 indexed citations

Tóth-Petróczy, Ágnes, et al.. (2024). Characterization of alternative splicing during mammalian brain development reveals the extent of isoform diversity and potential effects on protein structural changes. Biology Open. 13(10).

Chow, Chi Fung Willis, et al.. (2024). SHARK enables sensitive detection of evolutionary homologs and functional analogs in unalignable and disordered sequences. Proceedings of the National Academy of Sciences. 121(42). e2401622121–e2401622121. 5 indexed citations

Romero, Maria Luisa Romero, et al.. (2024). Environment modulates protein heterogeneity through transcriptional and translational stop codon readthrough. Nature Communications. 15(1). 4446–4446. 4 indexed citations

Landerer, Cedric, Maxim Scheremetjew, HongKee Moon, Lena Hersemann, & Ágnes Tóth-Petróczy. (2024). deTELpy: Python package for high-throughput detection of amino acid substitutions in mass spectrometry datasets. Bioinformatics. 40(7).

Landerer, Cedric, et al.. (2024). Fitness Effects of Phenotypic Mutations at Proteome-Scale Reveal Optimality of Translation Machinery. Molecular Biology and Evolution. 41(3). 3 indexed citations

Singh, Hari, et al.. (2024). PICNIC accurately predicts condensate-forming proteins regardless of their structural disorder across organisms. Nature Communications. 15(1). 10668–10668. 13 indexed citations

Adzhubei, Ivan, et al.. (2023). DeMAG predicts the effects of variants in clinically actionable genes by integrating structural and evolutionary epistatic features. Nature Communications. 14(1). 2230–2230. 8 indexed citations

Chow, Chi Fung Willis, Cedric Landerer, Rajat Ghosh, et al.. (2023). CD-CODE: crowdsourcing condensate database and encyclopedia. Nature Methods. 20(5). 673–676. 27 indexed citations

10.

Romero, Maria Luisa Romero, et al.. (2022). Phenotypic mutations contribute to protein diversity and shape protein evolution. Protein Science. 31(9). e4397–e4397. 8 indexed citations

11.

Tóth-Petróczy, Ágnes, Nikkola Carmichael, Elicia Estrella, et al.. (2019). Homozygous TRPV4 mutation causes congenital distal spinal muscular atrophy and arthrogryposis. Neurology Genetics. 5(2). e312–e312. 16 indexed citations

12.

Cvetešić, Nevena, et al.. (2019). On the Mechanism and Origin of Isoleucyl-tRNA Synthetase Editing against Norvaline. Journal of Molecular Biology. 431(6). 1284–1297. 17 indexed citations

13.

Hopf, Thomas A., Anna G. Green, Benjamin Schubert, et al.. (2018). The EVcouplings Python framework for coevolutionary sequence analysis. Bioinformatics. 35(9). 1582–1584. 172 indexed citations

14.

Laurino, Paola, Ágnes Tóth-Petróczy, Rubén Meana‐Pañeda, et al.. (2016). An Ancient Fingerprint Indicates the Common Ancestry of Rossmann-Fold Enzymes Utilizing Different Ribose-Based Cofactors. PLoS Biology. 14(3). e1002396–e1002396. 83 indexed citations

15.

Tóth-Petróczy, Ágnes, et al.. (2015). Systematic Mapping of Protein Mutational Space by Prolonged Drift Reveals the Deleterious Effects of Seemingly Neutral Mutations. PLoS Computational Biology. 11(8). e1004421–e1004421. 56 indexed citations

16.

Tóth-Petróczy, Ágnes & Dan S. Tawfik. (2014). The robustness and innovability of protein folds. Current Opinion in Structural Biology. 26. 131–138. 101 indexed citations

17.

Tóth-Petróczy, Ágnes, et al.. (2013). Correlated Occurrence and Bypass of Frame-Shifting Insertion-Deletions (InDels) to Give Functional Proteins. PLoS Genetics. 9(10). e1003882–e1003882. 37 indexed citations

18.

Hagai, Tzachi, Ágnes Tóth-Petróczy, Ariel Azia, & Yaakov Levy. (2012). The origins and evolution of ubiquitination sites. Molecular BioSystems. 8(7). 1865–1877. 23 indexed citations

19.

Tóth-Petróczy, Ágnes, Bálint Mészáros, István Simon, et al.. (2008). Assessing Conservation of Disordered Regions in Proteins. Digital Commons - University of South Florida (University of South Florida). 1(1). 46–53. 15 indexed citations

20.

Tóth-Petróczy, Ágnes, Christopher J. Oldfield, István Simon, et al.. (2008). Malleable Machines in Transcription Regulation: The Mediator Complex. PLoS Computational Biology. 4(12). e1000243–e1000243. 96 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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