Kaspar Märtens

1.9k citations
12 papers · 1.1k indexed · 1 hit paper · h-index 7
Topics
Statistical Methods and Bayesian Inference (2 papers)RNA modifications and cancer (2 papers)Bayesian Methods and Mixture Models (2 papers)

In The Last Decade

Kaspar Märtens

12 papers receiving 1.0k citations

Hit Papers

Bayesian statistics and modelling20212026202220242021200400600

Peers

Kaspar Märtens
Comparison fields: 5 of 185
  • Molecular Biology 363
  • Genetics 159
  • Artificial Intelligence 90
  • Cancer Research 62
  • Biomedical Engineering 51
Replace Colin S. Gillespie with:
Colin S. Gillespie United Kingdom
Kevin Flores United States
Bianca Kramer Netherlands
Duco Veen Netherlands
Joukje E. Willemsen Netherlands
C. Spearman
Osvaldo A. Martin Argentina
Peter Foster United Kingdom
Yoshitaka Sakamoto Japan
Fredrik Jönsson Sweden
Kaspar Märtens relative to Colin S. Gillespie United Kingdom Colin S. Gillespie's profile →
Citations per field
00.5×1.5×2.4×
Colin S. Gillespie · 1×
Citations per year

Countries citing papers authored by Kaspar Märtens

Since Specialization
Citations

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

Fields of papers citing papers by Kaspar Märtens

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kaspar Märtens

This figure shows the co-authorship network connecting the top 25 collaborators of Kaspar Märtens. A scholar is included among the top collaborators of Kaspar Märtens 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 Kaspar Märtens. Kaspar Märtens is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
#WorkIndexed citations
1 4
2 4
3
Bayesian statistics and modellingbreakdown →
616
4 19
5 56
6 2
7 4
8 1
9 29
10 25
11 26
12 286

About Kaspar Märtens

Kaspar Märtens is a scholar working on Statistics and Probability, Applied Psychology and Biophysics, having authored 12 papers that have together received 1.1k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (2 papers), RNA modifications and cancer (2 papers) and Bayesian Methods and Mixture Models (2 papers). The work is most often cited by research in Biophysics (35 citations), Statistics and Probability (48 citations) and Statistics, Probability and Uncertainty (41 citations). Kaspar Märtens has collaborated with scholars based in United Kingdom, Estonia and United States. Frequent co-authors include Christopher Yau, Andrew Gelman, Sarah Depaoli, Marina Vannucci, Joukje E. Willemsen, Mahlet G. Tadesse, Bianca Kramer, Ruth King, Rens van de Schoot and Duco Veen. Their work appears in journals such as Nature Communications, Bioinformatics and Genome 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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