Jan Benada

876 citations
16 papers · 591 · h-index 11

Impact in

  • Oncology top 10%
    • Cancer-related Molecular Pathways
    • PARP inhibition in cancer therapy
  • Cell Biology top 10%
    • Microtubule and mitosis dynamics

Papers in

    • DNA Repair Mechanisms 12
    • CRISPR and Genetic Engineering 4
    • Ubiquitin and proteasome pathways 3
    • Epigenetics and DNA Methylation 2
    • Genomics and Chromatin Dynamics 2
    • Cancer-related Molecular Pathways 6

Jan Benada

14 papers receiving 587 citations

Peers

Jan Benada
Comparison fields: 5 of 59
  • Oncology 237
  • Cell Biology 111
  • Molecular Biology 446
  • Cancer Research 85
  • Aging 8
Replace Jessica Vieusseux with:
Jessica Vieusseux Australia
Ekaterina Gresko Switzerland
Sabine Rottmann Germany
Weilin Xie China
William J. Muller Canada
Laurent Antoni United Kingdom
Galina Semenova United States
Nadia Barboule France
Vaishali Shinde United States
Karim Nacerddine United States
Jan Benada relative to Jessica Vieusseux Australia Jessica Vieusseux's profile →
Citations per field
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Jessica Vieusseux · 1×
Citations per year

Countries citing papers authored by Jan Benada

Since Specialization
Citations

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

Fields of papers citing papers by Jan Benada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 2013115
2 201591
3 201660
4 201558
5 202053
6 202249
7 201341
8 202237
9 201733
10 202318
11 202216
12 20237
13 20217
14 20226
15 20250
16 20250

About Jan Benada

Jan Benada is a scholar working on Molecular Biology, Oncology, Cell Biology, Pathology and Forensic Medicine and Geriatrics and Gerontology, having authored 16 papers that have together received 591 indexed citations. Recurring topics across this work include DNA Repair Mechanisms (12 papers), Cancer-related Molecular Pathways (6 papers), Microtubule and mitosis dynamics (5 papers), CRISPR and Genetic Engineering (4 papers), Ubiquitin and proteasome pathways (3 papers), Epigenetics and DNA Methylation (2 papers), Genomics and Chromatin Dynamics (2 papers) and Cytomegalovirus and herpesvirus research (1 paper). The work is most often cited by research in Oncology (237 citations), Cell Biology (111 citations), Molecular Biology (446 citations), Cancer Research (85 citations) and Aging (8 citations). Jan Benada has collaborated with scholars based in Denmark, Czechia and Netherlands. Frequent co-authors include Libor Macůrek, Kamila Burdová, Petra Kleiblová, Jiří Bártek, René H. Medema, Claus Storgaard Sørensen, Patrick von Morgen, Emile E. Voest, Pavel Dundr and Valdemaras Petrosius. Their work appears in journals such as Cell Reports, Cell Cycle, iScience, The Journal of Cell Biology and JCI Insight.

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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