Andrea Bommert

927 total citations · 1 hit paper
8 papers, 583 citations indexed

About

Andrea Bommert is a scholar working on Artificial Intelligence, Molecular Biology and Statistics and Probability. According to data from OpenAlex, Andrea Bommert has authored 8 papers receiving a total of 583 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 3 papers in Molecular Biology and 3 papers in Statistics and Probability. Recurrent topics in Andrea Bommert's work include Machine Learning and Data Classification (5 papers), Gene expression and cancer classification (3 papers) and Statistical Methods and Inference (2 papers). Andrea Bommert is often cited by papers focused on Machine Learning and Data Classification (5 papers), Gene expression and cancer classification (3 papers) and Statistical Methods and Inference (2 papers). Andrea Bommert collaborates with scholars based in Germany and Canada. Andrea Bommert's co-authors include Jörg Rahnenführer, Michel Lang, Bernd Bischl, Xudong Sun, Thomas Welchowski, Matthias Schmid, Franziska Kappenberg, Nicholas Schreck, Alla Slynko and Axel Benner and has published in prestigious journals such as PLoS ONE, Briefings in Bioinformatics and Computational Statistics & Data Analysis.

In The Last Decade

Andrea Bommert

7 papers receiving 569 citations

Hit Papers

align trajectories

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.

Benchmark for filter methods for feature selection in high-dimensional classification data

2019 458 citations Andrea Bommert, Xudong Sun et al. Computational Statistics & Data Analysis profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Andrea Bommert Germany	4	251	121	97	51	40	8	583
Utkarsh Mahadeo Khaire India	7	251 1.0×	75 0.6×	92 0.9×	37 0.7×	48 1.2×	13	516
Shih-Wen Ke Taiwan	7	244 1.0×	112 0.9×	66 0.7×	60 1.2×	29 0.7×	11	625
Pablo Bermejo Spain	10	336 1.3×	78 0.6×	136 1.4×	93 1.8×	29 0.7×	26	591
Minghao Piao South Korea	12	122 0.5×	108 0.9×	110 1.1×	59 1.2×	53 1.3×	39	726
Abdullah Almuhaimeed Saudi Arabia	13	194 0.8×	106 0.9×	105 1.1×	27 0.5×	26 0.7×	26	554
Rui Tang China	15	328 1.3×	60 0.5×	79 0.8×	87 1.7×	54 1.4×	44	675
Artur Ferreira Portugal	8	281 1.1×	97 0.8×	169 1.7×	70 1.4×	35 0.9×	31	607
Majdi Khalid Saudi Arabia	14	119 0.5×	78 0.6×	68 0.7×	34 0.7×	21 0.5×	42	405
Xuewen Chen United States	8	357 1.4×	71 0.6×	99 1.0×	65 1.3×	18 0.5×	19	507

Countries citing papers authored by Andrea Bommert

Since Specialization

Citations

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

Fields of papers citing papers by Andrea Bommert

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrea Bommert

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

All Works

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8 of 8 papers shown

1.

Bommert, Andrea, et al.. (2025). On the estimation of inverse-probability-of-censoring weights for the evaluation of survival prediction error. PLoS ONE. 20(1). e0318349–e0318349. 2 indexed citations

2.

Schreck, Nicholas, et al.. (2024). Simulation study to evaluate when Plasmode simulation is superior to parametric simulation in estimating the mean squared error of the least squares estimator in linear regression. PLoS ONE. 19(5). e0299989–e0299989. 2 indexed citations

3.

Bommert, Andrea, et al.. (2024). Smart Pallets: Towards Event Detection Using IMUs. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 1–4.

4.

Kappenberg, Franziska, et al.. (2024). Methods for quantifying dataset similarity: a review, taxonomy and comparison. 18(none). 3 indexed citations

5.

Bommert, Andrea, Thomas Welchowski, Matthias Schmid, & Jörg Rahnenführer. (2021). Benchmark of filter methods for feature selection in high-dimensional gene expression survival data. Briefings in Bioinformatics. 23(1). 103 indexed citations

6.

Bommert, Andrea & Michel Lang. (2021). stabm: Stability Measures for Feature Selection. The Journal of Open Source Software. 6(59). 3010–3010. 5 indexed citations

7.

Bommert, Andrea, Xudong Sun, Bernd Bischl, Jörg Rahnenführer, & Michel Lang. (2019). Benchmark for filter methods for feature selection in high-dimensional classification data. Computational Statistics & Data Analysis. 143. 106839–106839. 458 indexed citations breakdown →

8.

Bommert, Andrea, Jörg Rahnenführer, & Michel Lang. (2017). A Multicriteria Approach to Find Predictive and Sparse Models with Stable Feature Selection for High-Dimensional Data. Computational and Mathematical Methods in Medicine. 2017. 1–18. 10 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.

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