Jan Benada

842 citations
14 papers · 566 indexed · h-index 11
  • Oncology top 10%
    • Cancer-related Molecular Pathways 5
  • Cell Biology top 10%
    • Microtubule and mitosis dynamics 5
    • DNA Repair Mechanisms 12
    • CRISPR and Genetic Engineering 4
    • Ubiquitin and proteasome pathways 3
    • Epigenetics and DNA Methylation 3
    • Genomics and Chromatin Dynamics 2
    • Cancer therapeutics and mechanisms 1

Jan Benada

14 papers receiving 563 citations

Peers

Jan Benada
Comparison fields: 5 of 60
  • Oncology 245
  • Cell Biology 114
  • Molecular Biology 460
  • Cancer Research 96
  • Aging 8
Replace Ekaterina Gresko with:
Ekaterina Gresko Switzerland
Laurent Antoni United Kingdom
Peiguo Shi China
Zelda Lichtensztejn Canada
Gina M. Ney United States
Priya Aggarwal United States
JulieAnn Rader United States
Amanda R. Wasylishen United States
Dongxue Su China
Vaidehi Krishnan Singapore
Jan Benada relative to Ekaterina Gresko Switzerland Ekaterina Gresko's profile →
Citations per field
00.5×6.2×
Ekaterina Gresko · 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-authorship network

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

14 of 14 papers shown
#Work
1 20236
2 202315
3 20225
4 202235
5 202216
6 202246
7 20216
8 202050
9 201731
10 201659
11 201589
12 201556
13 201341
14 2013111

About Jan Benada

Jan Benada is a scholar working on Cell Biology, Geriatrics and Gerontology, Oncology, Molecular Biology and Cancer Research, having authored 14 papers that have together received 566 indexed citations. Recurring topics across this work include DNA Repair Mechanisms (12 papers), Cancer-related Molecular Pathways (5 papers), Microtubule and mitosis dynamics (5 papers), CRISPR and Genetic Engineering (4 papers), Ubiquitin and proteasome pathways (3 papers), Epigenetics and DNA Methylation (3 papers), Genomics and Chromatin Dynamics (2 papers) and Cancer therapeutics and mechanisms (1 paper). The work is most often cited by research in Oncology (245 citations), Cell Biology (114 citations), Molecular Biology (460 citations), Cancer Research (96 citations) and Aging (8 citations). Jan Benada has collaborated with scholars based in Denmark, Czechia and Sweden. Frequent co-authors include Libor Macůrek, Kamila Burdová, Petra Kleiblová, Jiří Bártek, René H. Medema, Claus Storgaard Sørensen, Patrick von Morgen, Gabriela Jeníková, Pavel Dundr and Emile E. Voest. Their work appears in journals such as Cell Cycle, Cell Reports, iScience, The EMBO Journal and The Journal of Cell Biology.

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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