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.
Chronic infection drives Dnmt3a-loss-of-function clonal hematopoiesis via IFNγ signaling
2021211 citationsPaweł Kuś, Roman Jaksik et al.profile →
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 Marek Kimmel'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 Marek Kimmel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marek Kimmel more than expected).
This network shows the impact of papers produced by Marek Kimmel. 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 Marek Kimmel. The network helps show where Marek Kimmel may publish in the future.
Co-authorship network of co-authors of Marek Kimmel
This figure shows the co-authorship network connecting the top 25 collaborators of Marek Kimmel.
A scholar is included among the top collaborators of Marek Kimmel 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 Marek Kimmel. Marek Kimmel is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Fujarewicz, Krzysztof, Marek Kimmel, Tomasz Lipniacki, & Andrzej Świerniak. (2006). Parameter estimation for models of cell signaling pathways based on semi-quantitative data. 306–310.
Cyran, Krzysztof A., Joanna Polańska, & Marek Kimmel. (2004). TESTING FOR SIGNATURES OF NATURAL SELECTION AT MOLECULAR GENES LEVEL. Journal of Medical Informatics & Technologies. 8.1 indexed citations
16.
Kimmel, Marek & Andrzej Świerniak. (2004). Using control theory to make cancer chemotherapy beneficial from phase dependence and resistant to drug resistance. Archives of Control Sciences. 14(2). 105–145.6 indexed citations
17.
Polański, Andrzej & Marek Kimmel. (2003). POPULATION GENETICS MODELS FOR THE STATISTICS OF DNA SAMPLES UNDER DIFFERENT DEMOGRAPHIC SCENARIOS—MAXIMUM LIKELIHOOD VERSUS APPROXIMATE METHODS. International Journal of Applied Mathematics and Computer Science. 13(3). 347–355.
18.
Świerniak, Andrzej, et al.. (1999). Qualitative analysis of controlled drug resistance model - inverse Laplace and and semigroup approach. Control and Cybernetics. 28(1). 61–73.21 indexed citations
19.
Bobrowski, Adam & Marek Kimmel. (1999). Dynamics of the life history of a DNA-repeat sequence. Archives of Control Sciences. 9. 57–67.3 indexed citations
20.
Kimmel, Marek. (1979). Mathematical model of the proliferation cycle of lymphoblastic leukemia cells.. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich). 10(2). 91–7.3 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.