Éva Schád

2.7k total citations
29 papers, 1.1k citations indexed

About

Éva Schád is a scholar working on Molecular Biology, Cell Biology and Materials Chemistry. According to data from OpenAlex, Éva Schád has authored 29 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Molecular Biology, 6 papers in Cell Biology and 5 papers in Materials Chemistry. Recurrent topics in Éva Schád's work include Protein Structure and Dynamics (10 papers), RNA Research and Splicing (8 papers) and Calpain Protease Function and Regulation (6 papers). Éva Schád is often cited by papers focused on Protein Structure and Dynamics (10 papers), RNA Research and Splicing (8 papers) and Calpain Protease Function and Regulation (6 papers). Éva Schád collaborates with scholars based in Hungary, Belgium and United Kingdom. Éva Schád's co-authors include Péter Tompa, Ágnes Tantos, Hédi Hegyi, Lajos Kalmár, Rita Pancsa, Bálint Mészáros, Zsuzsanna Dosztányi, Péter Friedrich, Beáta Szabó and Tamás Horváth and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Bioinformatics.

In The Last Decade

Éva Schád

28 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Éva Schád Hungary 16 936 177 172 100 69 29 1.1k
Agnieszka Lewandowska Poland 14 873 0.9× 213 1.2× 144 0.8× 43 0.4× 28 0.4× 23 1.1k
Charles A. Galea United States 18 848 0.9× 182 1.0× 155 0.9× 43 0.4× 65 0.9× 25 1.0k
Markus Seiler Germany 10 899 1.0× 156 0.9× 67 0.4× 111 1.1× 51 0.7× 11 1.0k
Jirka Peschek Germany 14 878 0.9× 221 1.2× 178 1.0× 87 0.9× 32 0.5× 23 1.0k
Alexander Miguel Monzón Italy 17 970 1.0× 54 0.3× 253 1.5× 66 0.7× 73 1.1× 43 1.1k
Raymond Mak United States 6 1.2k 1.3× 319 1.8× 74 0.4× 51 0.5× 174 2.5× 8 1.4k
Sachiko Takayama United States 9 663 0.7× 65 0.4× 133 0.8× 134 1.3× 37 0.5× 10 832
Galina A. Zhouravleva Russia 19 1.5k 1.6× 85 0.5× 74 0.4× 91 0.9× 18 0.3× 80 1.7k
Timothy J. Ragan United Kingdom 16 854 0.9× 70 0.4× 70 0.4× 120 1.2× 63 0.9× 26 1.1k
C.H.S. Aylett United Kingdom 17 937 1.0× 170 1.0× 95 0.6× 174 1.7× 55 0.8× 26 1.2k

Countries citing papers authored by Éva Schád

Since Specialization
Citations

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

Fields of papers citing papers by Éva Schád

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Éva Schád

This figure shows the co-authorship network connecting the top 25 collaborators of Éva Schád. A scholar is included among the top collaborators of Éva Schád 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 Éva Schád. Éva Schád 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.
Kiss, Csaba, Éva Bakos, Anna Lovrics, et al.. (2025). Therapy-induced senescence is a transient drug resistance mechanism in breast cancer. Molecular Cancer. 24(1). 128–128. 5 indexed citations
2.
Schád, Éva, et al.. (2024). Morphological Changes Induced by TKS4 Deficiency Can Be Reversed by EZH2 Inhibition in Colorectal Carcinoma Cells. Biomolecules. 14(4). 445–445. 1 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.
Schád, Éva, et al.. (2023). Absence of Scaffold Protein Tks4 Disrupts Several Signaling Pathways in Colon Cancer Cells. International Journal of Molecular Sciences. 24(2). 1310–1310. 3 indexed citations
5.
Szabó, Beáta, et al.. (2023). KMT2D preferentially binds mRNAs of the genes it regulates, suggesting a role in RNA processing. Protein Science. 33(1). e4847–e4847. 2 indexed citations
6.
Szabó, Beáta, et al.. (2023). In Vivo and In Vitro Characterization of the RNA Binding Capacity of SETD1A (KMT2F). International Journal of Molecular Sciences. 24(22). 16032–16032. 1 indexed citations
7.
Schád, Éva, Ágnes Révész, Lilla Turiák, et al.. (2022). Identification of Intrinsically Disordered Proteins and Regions in a Non-Model Insect Species Ostrinia nubilalis (Hbn.). Biomolecules. 12(4). 592–592. 5 indexed citations
8.
Mészáros, Bálint, Gábor Erdős, Beáta Szabó, et al.. (2019). PhaSePro: the database of proteins driving liquid–liquid phase separation. Nucleic Acids Research. 48(D1). D360–D367. 138 indexed citations
9.
Szabó, Beáta, Tamás Horváth, Éva Schád, et al.. (2019). Intrinsically Disordered Linkers Impart Processivity on Enzymes by Spatial Confinement of Binding Domains. International Journal of Molecular Sciences. 20(9). 2119–2119. 13 indexed citations
10.
Pancsa, Rita, Éva Schád, Ágnes Tantos, & Péter Tompa. (2019). Emergent functions of proteins in non-stoichiometric supramolecular assemblies. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics. 1867(10). 970–979. 52 indexed citations
11.
Lázár, Tamás, Mainak Guharoy, Éva Schád, & Péter Tompa. (2018). Unique Physicochemical Patterns of Residues in Protein–Protein Interfaces. Journal of Chemical Information and Modeling. 58(10). 2164–2173. 6 indexed citations
12.
Piovesan, Damiano, Francesco Tabaro, Lisanna Paladin, et al.. (2017). MobiDB 3.0: more annotations for intrinsic disorder, conformational diversity and interactions in proteins. Nucleic Acids Research. 46(D1). D471–D476. 142 indexed citations
13.
Lázár, Tamás, Éva Schád, Beáta Szabó, et al.. (2016). Intrinsic protein disorder in histone lysine methylation. Biology Direct. 11(1). 30–30. 17 indexed citations
14.
Tompa, Péter, Éva Schád, Ágnes Tantos, & Lajos Kalmár. (2015). Intrinsically disordered proteins: emerging interaction specialists. Current Opinion in Structural Biology. 35. 49–59. 168 indexed citations
15.
Schád, Éva, Péter Tompa, & Hédi Hegyi. (2011). The relationship between proteome size, structural disorder and organism complexity. Genome biology. 12(12). R120–R120. 155 indexed citations
16.
Hegyi, Hédi, Éva Schád, & Péter Tompa. (2007). Structural disorder promotes assembly of protein complexes. BMC Structural Biology. 7(1). 65–65. 75 indexed citations
17.
Tompa, Péter, Éva Schád, & Péter Friedrich. (2003). A Sensitive and Continuous Fluorometric Activity Assay Using a Natural Substrate: Microtubule-Associated Protein 2. Humana Press eBooks. 144. 137–141. 3 indexed citations
18.
Schád, Éva, et al.. (2002). A novel human small subunit of calpains. Biochemical Journal. 362(2). 383–388. 19 indexed citations
19.
Schád, Éva, Attila E. Farkas, Gáspár Jékely, Péter Tompa, & Péter Friedrich. (2002). A novel human small subunit of calpains. Biochemical Journal. 362(2). 383–383. 36 indexed citations
20.
Tompa, Péter, Éva Schád, Andrea Baki, et al.. (1995). An Ultrasensitive, Continuous Fluorometric Assay for Calpain Activity. Analytical Biochemistry. 228(2). 287–293. 19 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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