Hana Kovářová

1.9k citations
81 papers · 1.6k · h-index 20

Impact in

Papers in

    • Bacillus and Francisella bacterial research 7
    • Bioinformatics and Genomic Networks 6
    • Ubiquitin and proteasome pathways 5
    • Advanced Proteomics Techniques and Applications 16

Hana Kovářová

76 papers receiving 1.5k citations

Peers

Hana Kovářová
Comparison fields: 5 of 116
  • Molecular Biology 925
  • Developmental Neuroscience 43
  • Reproductive Medicine 87
  • Genetics 101
  • Spectroscopy 170
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Gereon Poschmann Germany
Inmaculada Jorge Spain
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Charles C. King United States
Sven C.D. van IJzendoorn Netherlands
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Citations per field
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Citations per year

Countries citing papers authored by Hana Kovářová

Since Specialization
Citations

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

Fields of papers citing papers by Hana Kovářová

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Hana Kovářová, 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 Hana Kovářová Line = papers co-authored together Hana Kovářová links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 81 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003253
2 2010167
3 2018124
4 200483
5 201276
6 201075
7 200044
8 202140
9 200736
10 199633
11 200728
12 201928
13 200527
14 200827
15 200225
16 200724
17 200923
18 201623
19 200820
20 201220

About Hana Kovářová

Hana Kovářová is a scholar working on Molecular Biology, Spectroscopy, Public Health, Environmental and Occupational Health, Radiology, Nuclear Medicine and Imaging and Cell Biology, having authored 81 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (16 papers), Reproductive Biology and Fertility (8 papers), Bacillus and Francisella bacterial research (7 papers), Microtubule and mitosis dynamics (6 papers), Bioinformatics and Genomic Networks (6 papers), Ubiquitin and proteasome pathways (5 papers), Monoclonal and Polyclonal Antibodies Research (5 papers) and Cancer-related Molecular Pathways (5 papers). The work is most often cited by research in Molecular Biology (925 citations), Developmental Neuroscience (43 citations), Reproductive Medicine (87 citations), Genetics (101 citations) and Spectroscopy (170 citations). Hana Kovářová has collaborated with scholars based in Czechia, United States and Germany. Frequent co-authors include Suresh Jivan Gadher, Jan Motlík, Helena Kupcová Skalníková, Zuzana Kročová, Igor Golovliov, Petr Halada, Anders Sjöstedt, Vladimir Baranov, Zdeňka Ellederová and Michal Kubelka. Their work appears in journals such as PROTEOMICS, Electrophoresis, Journal of Proteome Research, Journal of Proteomics and Technology in Cancer Research & Treatment.

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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