Julia K. Varga

1.6k total citations · 1 hit paper
16 papers, 427 citations indexed

About

Julia K. Varga is a scholar working on Molecular Biology, Spectroscopy and Pollution. According to data from OpenAlex, Julia K. Varga has authored 16 papers receiving a total of 427 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 3 papers in Spectroscopy and 1 paper in Pollution. Recurrent topics in Julia K. Varga's work include RNA and protein synthesis mechanisms (8 papers), Machine Learning in Bioinformatics (7 papers) and Protein Structure and Dynamics (6 papers). Julia K. Varga is often cited by papers focused on RNA and protein synthesis mechanisms (8 papers), Machine Learning in Bioinformatics (7 papers) and Protein Structure and Dynamics (6 papers). Julia K. Varga collaborates with scholars based in Israel, Hungary and United States. Julia K. Varga's co-authors include Ora Schueler‐Furman, Orly Avraham, Alisa Khramushin, Ziv Ben-Aharon, Tomer Tsaban, Gábor Tusnády, Roland Ludwig, Clemens Peterbauer, Dietmar Haltrich and Klaus D. Kulbe and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Angewandte Chemie International Edition.

In The Last Decade

Julia K. Varga

16 papers receiving 424 citations

Hit Papers

Harnessing protein folding neural networks for peptide–pr... 2022 2026 2023 2024 2022 50 100 150 200
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.

  1. Harnessing protein folding neural networks for peptide–protein docking
    2022 211 citations Tomer Tsaban, Julia K. Varga et al. Nature Communications profile →

Peers

Julia K. Varga
Marcus Bäck Sweden
Pooja Suresh United States
Victor Sivozhelezov Russia
Orly Avraham Israel
Vy Nguyen United States
Chuanqi Sun China
Xiaodan Ni United States
Nhan T. Pham United Kingdom
Marcus Bäck Sweden
Julia K. Varga
Citations per year, relative to Julia K. Varga Julia K. Varga (= 1×) peers Marcus Bäck

Countries citing papers authored by Julia K. Varga

Since Specialization
Citations

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

Fields of papers citing papers by Julia K. Varga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Julia K. Varga. 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 Julia K. Varga. The network helps show where Julia K. Varga may publish in the future.

Co-authorship network of co-authors of Julia K. Varga

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

All Works

16 of 16 papers shown
1.
Varga, Julia K., Sergey Ovchinnikov, & Ora Schueler‐Furman. (2025). actifpTM: a refined confidence metric of AlphaFold2 predictions involving flexible regions. Bioinformatics. 41(3). 9 indexed citations
2.
Kruse, Thomas, Dimitriya H. Garvanska, Julia K. Varga, et al.. (2024). Substrate recognition principles for the PP2A-B55 protein phosphatase. Science Advances. 10(40). eadp5491–eadp5491. 10 indexed citations
3.
Varga, Julia K., Christian Schäfer, M Welzel, et al.. (2024). Systematic discovery of protein interaction interfaces using AlphaFold and experimental validation. Molecular Systems Biology. 20(2). 75–97. 41 indexed citations
4.
Varga, Julia K., Shahar Rotem‐Bamberger, Einav Cohen‐Kfir, et al.. (2023). Structural study of UFL1‐UFC1 interaction uncovers the role of UFL1 N‐terminal helix in ufmylation. EMBO Reports. 24(12). e56920–e56920. 12 indexed citations
5.
Varga, Julia K. & Ora Schueler‐Furman. (2023). Who Binds Better? Let Alphafold2 Decide!. Angewandte Chemie International Edition. 62(28). e202303526–e202303526. 2 indexed citations
6.
Khramushin, Alisa, Ziv Ben-Aharon, Tomer Tsaban, et al.. (2022). Matching protein surface structural patches for high-resolution blind peptide docking. Proceedings of the National Academy of Sciences. 119(18). e2121153119–e2121153119. 18 indexed citations
7.
Tsaban, Tomer, Julia K. Varga, Orly Avraham, et al.. (2022). Harnessing protein folding neural networks for peptide–protein docking. Nature Communications. 13(1). 176–176. 211 indexed citations breakdown →
8.
9.
Tálas, András, Krisztina Huszár, Péter István Kulcsár, et al.. (2021). A method for characterizing Cas9 variants via a one-million target sequence library of self-targeting sgRNAs. Nucleic Acids Research. 49(6). e31–e31. 12 indexed citations
10.
Turiák, Lilla, Julia K. Varga, György Várady, et al.. (2020). Partial proteolysis improves the identification of the extracellular segments of transmembrane proteins by surface biotinylation. Scientific Reports. 10(1). 8880–8880. 3 indexed citations
11.
Varga, Julia K. & Gábor Tusnády. (2019). The TMCrys server for supporting crystallization of transmembrane proteins. Bioinformatics. 35(20). 4203–4204. 2 indexed citations
12.
Varga, Julia K. & Gábor Tusnády. (2018). TMCrys: predict propensity of success for transmembrane protein crystallization. Bioinformatics. 34(18). 3126–3130. 5 indexed citations
13.
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
14.
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
15.
Varga, Julia K., László Dobson, & Gábor Tusnády. (2016). TOPDOM: database of conservatively located domains and motifs in proteins. Bioinformatics. 32(17). 2725–2726. 3 indexed citations
16.
Ludwig, Roland, et al.. (2004). Characterisation of cellobiose dehydrogenases from the white-rot fungi Trametes pubescens and Trametes villosa. Applied Microbiology and Biotechnology. 64(2). 213–222. 59 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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