László Dobson

1.9k total citations
26 papers, 862 citations indexed

About

László Dobson is a scholar working on Molecular Biology, Spectroscopy and Materials Chemistry. According to data from OpenAlex, László Dobson has authored 26 papers receiving a total of 862 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 4 papers in Spectroscopy and 3 papers in Materials Chemistry. Recurrent topics in László Dobson's work include RNA and protein synthesis mechanisms (18 papers), Machine Learning in Bioinformatics (16 papers) and Protein Structure and Dynamics (12 papers). László Dobson is often cited by papers focused on RNA and protein synthesis mechanisms (18 papers), Machine Learning in Bioinformatics (16 papers) and Protein Structure and Dynamics (12 papers). László Dobson collaborates with scholars based in Hungary, Germany and Belgium. László Dobson's co-authors include Gábor Tusnády, István Reményi, András Zeke, Bálint Mészáros, Toby J. Gibson, Sushama Michael, Norman E. Davey, Hugo Sámano‐Sánchez, Lucía B. Chemes and Tamás Lázár and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and Journal of Molecular Biology.

In The Last Decade

László Dobson

24 papers receiving 856 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
László Dobson Hungary 13 663 76 73 71 68 26 862
Timothy Nugent Ireland 17 845 1.3× 153 2.0× 49 0.7× 75 1.1× 86 1.3× 43 1.3k
Fatma Guettou Sweden 6 495 0.7× 89 1.2× 48 0.7× 35 0.5× 81 1.2× 6 745
Vincent G. Nadeau Canada 4 463 0.7× 79 1.0× 41 0.6× 53 0.7× 69 1.0× 6 672
István Reményi Hungary 6 384 0.6× 49 0.6× 40 0.5× 39 0.5× 50 0.7× 6 518
Sadhna Phanse Canada 18 947 1.4× 212 2.8× 92 1.3× 106 1.5× 38 0.6× 45 1.2k
Matthew Bashton United Kingdom 13 853 1.3× 85 1.1× 40 0.5× 37 0.5× 60 0.9× 26 1.1k
Igor A. Krasheninnikov Russia 19 1.2k 1.8× 90 1.2× 29 0.4× 85 1.2× 58 0.9× 44 1.3k
Stephen McCraith United States 10 838 1.3× 70 0.9× 55 0.8× 108 1.5× 85 1.3× 16 1.1k
Tobias Hamp Germany 8 585 0.9× 83 1.1× 26 0.4× 46 0.6× 93 1.4× 10 776
Mariana Gallo Italy 16 524 0.8× 39 0.5× 26 0.4× 70 1.0× 144 2.1× 56 783

Countries citing papers authored by László Dobson

Since Specialization
Citations

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

Fields of papers citing papers by László Dobson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of László Dobson

This figure shows the co-authorship network connecting the top 25 collaborators of László Dobson. A scholar is included among the top collaborators of László Dobson 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 László Dobson. László Dobson 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
1.
Dobson, László, Gábor Tusnády, & Péter Tompa. (2025). Regularly updated benchmark sets for statistically correct evaluations of AlphaFold applications. Briefings in Bioinformatics. 26(2).
2.
Zeke, András, Toby J. Gibson, & László Dobson. (2024). Linear motifs regulating protein secretion, sorting and autophagy in Leishmania parasites are diverged with respect to their host equivalents. PLoS Computational Biology. 20(2). e1011902–e1011902. 2 indexed citations
3.
Fichó, Erzsébet, Rita Pancsa, Csaba Magyar, et al.. (2024). MFIB 2.0: a major update of the database of protein complexes formed by mutual folding of the constituting protein chains. Nucleic Acids Research. 53(D1). D487–D494.
4.
Tusnády, Gábor, et al.. (2023). How AlphaFold2 shaped the structural coverage of the human transmembrane proteome. Scientific Reports. 13(1). 20283–20283. 13 indexed citations
5.
Tusnády, Gábor, András Zeke, Zsófia E. Kálmán, et al.. (2023). LeishMANIAdb: a comparative resource for Leishmania proteins. Database. 2023. 2 indexed citations
6.
Dobson, László, et al.. (2023). UniTmp: unified resources for transmembrane proteins. Nucleic Acids Research. 52(D1). D572–D578. 11 indexed citations
7.
Dobson, László, et al.. (2022). TmAlphaFold database: membrane localization and evaluation of AlphaFold2 predicted alpha-helical transmembrane protein structures. Nucleic Acids Research. 51(D1). D517–D522. 44 indexed citations
8.
Michael, Sushama, Bálint Mészáros, Hugo Sámano‐Sánchez, et al.. (2021). The Eukaryotic Linear Motif resource: 2022 release. Nucleic Acids Research. 50(D1). D497–D508. 153 indexed citations
9.
Kálmán, Zsófia E., Bálint Mészáros, Zoltán Gáspári, & László Dobson. (2020). Distribution of disease-causing germline mutations in coiled-coils implies an important role of their N-terminal region. Scientific Reports. 10(1). 17333–17333. 5 indexed citations
10.
Jarnot, Patryk, László Dobson, Matthew Merski, et al.. (2020). PlaToLoCo: the first web meta-server for visualization and annotation of low complexity regions in proteins. Nucleic Acids Research. 48(W1). W77–W84. 74 indexed citations
11.
12.
Mészáros, Bálint, László Dobson, Erzsébet Fichó, et al.. (2019). Sequential, Structural and Functional Properties of Protein Complexes Are Defined by How Folding and Binding Intertwine. Journal of Molecular Biology. 431(22). 4408–4428. 12 indexed citations
13.
Dobson, László, Bálint Mészáros, & Gábor Tusnády. (2018). Structural Principles Governing Disease-Causing Germline Mutations. Journal of Molecular Biology. 430(24). 4955–4970. 8 indexed citations
14.
Róna, Gergely, Éva Hunyadi‐Gulyás, Lilla Turiák, et al.. (2017). Identification of Extracellular Segments by Mass Spectrometry Improves Topology Prediction of Transmembrane Proteins. Scientific Reports. 7(1). 42610–42610. 15 indexed citations
15.
Varga, Julia K., László Dobson, István Reményi, & Gábor Tusnády. (2016). TSTMP: target selection for structural genomics of human transmembrane proteins. Nucleic Acids Research. 45(D1). D325–D330. 14 indexed citations
16.
Dobson, László, László Nyitray, & Zoltán Gáspári. (2015). A conserved charged single α-helix with a putative steric role in paraspeckle formation. RNA. 21(12). 2023–2029. 12 indexed citations
17.
Dobson, László, István Reményi, & Gábor Tusnády. (2015). The human transmembrane proteome. Biology Direct. 10(1). 31–31. 97 indexed citations
18.
Dobson, László, István Reményi, & Gábor Tusnády. (2015). CCTOP: a Consensus Constrained TOPology prediction web server. Nucleic Acids Research. 43(W1). W408–W412. 310 indexed citations
19.
Tusnády, Gábor, László Dobson, & Péter Tompa. (2015). Disordered regions in transmembrane proteins. Biochimica et Biophysica Acta (BBA) - Biomembranes. 1848(11). 2839–2848. 24 indexed citations
20.
Dobson, László, et al.. (2014). Expediting topology data gathering for the TOPDB database. Nucleic Acids Research. 43(D1). D283–D289. 33 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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