Thorsten Dickhaus

4.0k total citations · 1 hit paper
67 papers, 2.6k citations indexed

About

Thorsten Dickhaus is a scholar working on Statistics and Probability, Genetics and Molecular Biology. According to data from OpenAlex, Thorsten Dickhaus has authored 67 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Statistics and Probability, 14 papers in Genetics and 9 papers in Molecular Biology. Recurrent topics in Thorsten Dickhaus's work include Statistical Methods in Clinical Trials (23 papers), Statistical Methods and Inference (13 papers) and Statistical Methods and Bayesian Inference (10 papers). Thorsten Dickhaus is often cited by papers focused on Statistical Methods in Clinical Trials (23 papers), Statistical Methods and Inference (13 papers) and Statistical Methods and Bayesian Inference (10 papers). Thorsten Dickhaus collaborates with scholars based in Germany, Spain and Sweden. Thorsten Dickhaus's co-authors include Benjamin Blankertz, Klaus‐Robert Müller, Claudia Sannelli, Steven Lemm, Sebastian Halder, Christa Meisinger, Wolfgang Rathmann, Andreas Mielck, Dan Ziegler and Eva Maria Hammer and has published in prestigious journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Thorsten Dickhaus

64 papers receiving 2.6k citations

Hit Papers

Neurophysiological predictor of SMR-based BCI performance 2010 2026 2015 2020 2010 100 200 300 400 500
What are hit papers?

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.

  1. Neurophysiological predictor of SMR-based BCI performance
    2010 521 citations Benjamin Blankertz, Claudia Sannelli et al. NeuroImage profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Thorsten Dickhaus Germany 18 1.4k 535 397 329 262 67 2.6k
Olivier Colliot France 39 1.8k 1.3× 392 0.7× 1.4k 3.6× 578 1.8× 44 0.2× 156 6.5k
John A. D. Aston United Kingdom 25 1.2k 0.9× 254 0.5× 151 0.4× 115 0.3× 412 1.6× 107 3.2k
Carlton Chu United Kingdom 19 1.9k 1.4× 292 0.5× 646 1.6× 293 0.9× 70 0.3× 30 3.7k
Daniel S. Marcus United States 23 1.7k 1.2× 157 0.3× 663 1.7× 226 0.7× 47 0.2× 60 4.4k
Soumya Ghosh Australia 32 1.5k 1.1× 451 0.8× 85 0.2× 334 1.0× 29 0.1× 146 2.9k
Philippe Gervais France 17 851 0.6× 314 0.6× 380 1.0× 224 0.7× 20 0.1× 37 2.5k
Alexandros T. Tzallas Greece 31 1.9k 1.4× 288 0.5× 192 0.5× 493 1.5× 6 0.0× 173 3.8k
Yi Wu China 27 387 0.3× 232 0.4× 165 0.4× 192 0.6× 14 0.1× 126 2.4k
Valentina Moskvina United Kingdom 35 488 0.4× 450 0.8× 383 1.0× 95 0.3× 131 0.5× 61 3.9k
Hui Shen China 35 3.0k 2.2× 187 0.3× 96 0.2× 210 0.6× 8 0.0× 163 4.6k

Countries citing papers authored by Thorsten Dickhaus

Since Specialization
Citations

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

Fields of papers citing papers by Thorsten Dickhaus

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thorsten Dickhaus

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

All Works

20 of 20 papers shown
1.
Dickhaus, Thorsten, et al.. (2023). Multiple multi‐sample testing under arbitrary covariance dependency. Statistics in Medicine. 42(17). 2944–2961. 1 indexed citations
2.
Dickhaus, Thorsten, et al.. (2023). Multiple testing of composite null hypotheses for discrete data using randomized p‐values. Biometrical Journal. 66(1). e2300077–e2300077.
3.
Dickhaus, Thorsten, et al.. (2023). Long-term temporal evolution of extreme temperature in a warming Earth. PLoS ONE. 18(2). e0280503–e0280503. 1 indexed citations
4.
Dickhaus, Thorsten, et al.. (2022). Variability and extremes: statistical validation of the Alfred Wegener Institute Earth System Model (AWI-ESM). Geoscientific model development. 15(4). 1803–1820. 6 indexed citations
5.
Dickhaus, Thorsten, et al.. (2021). Variability and extremes: Statistical validation of the AWI-ESM. 2 indexed citations
6.
Dickhaus, Thorsten, et al.. (2021). On the usage of randomized p-values in the Schweder–Spjøtvoll estimator. Annals of the Institute of Statistical Mathematics. 74(2). 289–319. 2 indexed citations
7.
Dickhaus, Thorsten, et al.. (2020). Optimizing effective numbers of tests by vine copula modeling. SHILAP Revista de lepidopterología. 1 indexed citations
8.
9.
Kloft, Marius, Juan Antonio Rodríguez, Sören Sonnenburg, et al.. (2016). Combining Multiple Hypothesis Testing with Machine Learning Increases the Statistical Power of Genome-wide Association Studies. Scientific Reports. 6(1). 36671–36671. 47 indexed citations
10.
Olek, Sven, et al.. (2015). Simultaneous Statistical Inference for Epigenetic Data. PLoS ONE. 10(5). e0125587–e0125587. 5 indexed citations
11.
Heinrich, Verena, Tom Kamphans, Jens Stange, et al.. (2013). Estimating exome genotyping accuracy by comparing to data from large scale sequencing projects. Genome Medicine. 5(7). 69–69. 14 indexed citations
12.
Schreuder, Martijn, Johannes Höhne, Benjamin Blankertz, et al.. (2013). Optimizing event-related potential based brain–computer interfaces: a systematic evaluation of dynamic stopping methods. Journal of Neural Engineering. 10(3). 36025–36025. 76 indexed citations
13.
Dickhaus, Thorsten, Klaus Straßburger, Daniel Schunk, et al.. (2012). How to analyze many contingency tables simultaneously in genetic association studies. Statistical Applications in Genetics and Molecular Biology. 11(4). 27 indexed citations
14.
Heinrich, Verena, Jens Stange, Thorsten Dickhaus, et al.. (2011). The allele distribution in next-generation sequencing data sets is accurately described as the result of a stochastic branching process. Nucleic Acids Research. 40(6). 2426–2431. 30 indexed citations
15.
Sehouli, Jalid, Christoph Loddenkemper, Tatjana I. Cornu, et al.. (2011). Epigenetic quantification of tumor-infiltrating T-lymphocytes. Epigenetics. 6(2). 236–246. 64 indexed citations
16.
Hammer, Eva Maria, Sebastian Halder, Benjamin Blankertz, et al.. (2011). Psychological predictors of SMR-BCI performance. Biological Psychology. 89(1). 80–86. 213 indexed citations
17.
Haufe, Stefan, Ryota Tomioka, Thorsten Dickhaus, et al.. (2010). Large-scale EEG/MEG source localization with spatial flexibility. NeuroImage. 54(2). 851–859. 74 indexed citations
18.
Ziegler, Dan, Wolfgang Rathmann, Thorsten Dickhaus, Christa Meisinger, & Andreas Mielck. (2009). Neuropathic Pain in Diabetes, Prediabetes and Normal Glucose Tolerance: The MONICA/KORA Augsburg Surveys S2 and S3. Pain Medicine. 10(2). 393–400. 182 indexed citations
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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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