Éva Szakács

59 total papers · 668 total citations
32 papers, 395 citations indexed

About

Éva Szakács is a scholar working on Plant Science, Molecular Biology and Agronomy and Crop Science. According to data from OpenAlex, Éva Szakács has authored 32 papers receiving a total of 395 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Plant Science, 9 papers in Molecular Biology and 7 papers in Agronomy and Crop Science. Recurrent topics in Éva Szakács's work include Wheat and Barley Genetics and Pathology (24 papers), Plant Disease Resistance and Genetics (14 papers) and Chromosomal and Genetic Variations (10 papers). Éva Szakács is often cited by papers focused on Wheat and Barley Genetics and Pathology (24 papers), Plant Disease Resistance and Genetics (14 papers) and Chromosomal and Genetic Variations (10 papers). Éva Szakács collaborates with scholars based in Hungary, Czechia and Egypt. Éva Szakács's co-authors include Márta Molnár‐Láng, István Molnár, A. Schneider, Marianna Rakszegi, Gabriella Linc, András Cseh, Z. Bedö, Beáta Barnabás, Б. Барнабас and I. Karsaï and has published in prestigious journals such as Scientific Reports, International Journal of Molecular Sciences and Frontiers in Plant Science.

In The Last Decade

Éva Szakács

31 papers receiving 377 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Éva Szakács 374 105 73 41 14 32 395
Xiyun Song 304 0.8× 117 1.1× 91 1.2× 38 0.9× 14 1.0× 37 360
Zanping Han 307 0.8× 109 1.0× 75 1.0× 49 1.2× 9 0.6× 19 347
Moju Cao 316 0.8× 101 1.0× 53 0.7× 38 0.9× 24 1.7× 20 364
Jinghuan Zhu 316 0.8× 95 0.9× 106 1.5× 37 0.9× 15 1.1× 30 361
Tan Kehui 357 1.0× 187 1.8× 27 0.4× 36 0.9× 11 0.8× 21 388
Parmeshwar K. Sahu 333 0.9× 91 0.9× 63 0.9× 18 0.4× 10 0.7× 41 367
Baoshen Liu 299 0.8× 127 1.2× 123 1.7× 42 1.0× 4 0.3× 30 345
Piwu Wang 339 0.9× 208 2.0× 91 1.2× 34 0.8× 18 1.3× 38 434
Hong Di 350 0.9× 108 1.0× 143 2.0× 49 1.2× 9 0.6× 30 390
Kangjing Liang 394 1.1× 176 1.7× 117 1.6× 16 0.4× 8 0.6× 30 444

Countries citing papers authored by Éva Szakács

Since Specialization
Citations

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

Fields of papers citing papers by Éva Szakács

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Éva Szakács

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

All Works

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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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