Gergely Csaba

1.5k citations
39 papers · 1.0k · h-index 16

Impact in

    • RNA Research and Splicing
    • Bioinformatics and Genomic Networks
    • Protein Structure and Dynamics
    • RNA and protein synthesis mechanisms
    • RNA modifications and cancer
    • Genomics and Phylogenetic Studies
    • MicroRNA in disease regulation

Papers in

    • Protein Structure and Dynamics 5
    • Bioinformatics and Genomic Networks 5
    • RNA Research and Splicing 3
    • Heat shock proteins research 2
    • Gene expression and cancer classification 2
    • Diet and metabolism studies 3

Gergely Csaba

35 papers receiving 988 citations

Peers

Gergely Csaba
Comparison fields: 5 of 95
  • Molecular Biology 656
  • Cancer Research 129
  • Biochemistry 61
  • Nutrition and Dietetics 109
  • Immunology 101
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Citations per field
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Citations per year

Countries citing papers authored by Gergely Csaba

Since Specialization
Citations

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

Fields of papers citing papers by Gergely Csaba

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Gergely Csaba, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gergely Csaba Line = papers co-authored together Gergely Csaba links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016196
2 200791
3 201987
4 201982
5 201065
6 201855
7 200955
8 201152
9 201651
10 200745
11 201539
12 200833
13 201530
14 201924
15 201919
16 201317
17 201311
18 201211
19 20247
20 20195

About Gergely Csaba

Gergely Csaba is a scholar working on Molecular Biology, Physiology, Cell Biology, Nutrition and Dietetics and Spectroscopy, having authored 39 papers that have together received 1.0k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (5 papers), Bioinformatics and Genomic Networks (5 papers), Endoplasmic Reticulum Stress and Disease (3 papers), RNA Research and Splicing (3 papers), Diet and metabolism studies (3 papers), Advanced Proteomics Techniques and Applications (2 papers), Heat shock proteins research (2 papers) and Gene expression and cancer classification (2 papers). The work is most often cited by research in Molecular Biology (656 citations), Cancer Research (129 citations), Biochemistry (61 citations), Nutrition and Dietetics (109 citations) and Immunology (101 citations). Gergely Csaba has collaborated with scholars based in Germany, Hungary and United States. Frequent co-authors include Ralf Zimmer, Fabian Birzele, Ludwig Geistlinger, Robert Küffner, Martin Haslbeck, Haroon Naeem, Oliver Soehnlein, Yvonne Döring, Yvonne Jansen and Christian Weber. Their work appears in journals such as Bioinformatics, BMC Bioinformatics, PLoS ONE, Nucleic Acids Research and Journal of Proteome Research.

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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