Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Estimation of nuclear DNA content in plants using flow cytometry
20071.2k citationsJaroslav Doležel, Johann Greilhuber et al.profile →
The more the better? The role of polyploidy in facilitating plant invasions
2011656 citationsJan Suda, Magdalena Kubešová et al.Annals of Botanyprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Jan Suda'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 Suda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Suda more than expected).
This network shows the impact of papers produced by Jan Suda. 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 Suda. The network helps show where Jan Suda may publish in the future.
Co-authorship network of co-authors of Jan Suda
This figure shows the co-authorship network connecting the top 25 collaborators of Jan Suda.
A scholar is included among the top collaborators of Jan Suda 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 Jan Suda. Jan Suda is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Kolář, Filip, Zdeněk Kaplan, Jan Suda, & Milan Štech. (2015). Populations of Knautia in ecologically distinct refugia on the Hercynian massif belong to two endemic species.. Preslia. 87(4). 363–386.8 indexed citations
7.
Vít, Petr, et al.. (2014). Interspecific hybridization between rare and common plant congeners inferred from genome size data: assessing the threat to the Czech serpentine endemic Cerastium alsinifolium.. Preslia. 86(1). 95–117.14 indexed citations
Suda, Jan & Petr Pyšek. (2010). Special Issue: Flow cytometry in botanical research.. Preslia. 82(1). 1–163.6 indexed citations
12.
Loureiro, João, Pavel Trávníček, Jana Rauchová, et al.. (2010). The use of flow cytometry in the biosystematics, ecology and population biology of homoploid plants.. Preslia. 82(1). 3–21.72 indexed citations
13.
Dušková, Eva, Filip Kolář, Petr Sklenář, et al.. (2010). Genome size correlates with growth form, habitat and phylogeny in the Andean genus Lasiocephalus (Asteraceae).. Preslia. 82(1). 127–148.52 indexed citations
14.
Trávníček, Pavel, et al.. (2010). The distribution of cytotypes of Vicia cracca in Central Europe: the changes that have occurred over the last four decades.. Preslia. 82(1). 149–163.30 indexed citations
15.
Suda, Jan, Pavel Trávníček, Bohumil Mandák, Kateřina Berchová‐Bímová, & Petr Pyšek. (2010). Genome size as a marker for identifying the invasive alien taxa in Fallopia section Reynoutria.. Preslia. 82(1). 97–106.32 indexed citations
Kubešová, Magdalena, Lenka Moravcová, Jan Suda, V. Jarošík, & Petr Pyšek. (2010). Naturalized plants have smaller genomes than their non-invading relatives: a flow cytometric analysis of the Czech alien flora.. Preslia. 82(1). 81–96.110 indexed citations
18.
Duchoslav, Martin, et al.. (2010). Cytotype distribution in mixed populations of polyploid Allium oleraceum measured at a microgeographic scale.. Preslia. 82(1). 107–126.25 indexed citations
19.
Doležel, Jaroslav, Johann Greilhuber, & Jan Suda. (2007). Flow cytometry with plant cells : analysis of genes, chromosomes and genomes. Wiley-VCH eBooks.119 indexed citations
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.