Michael G. Schimek

1.5k total citations
38 papers, 761 citations indexed

About

Michael G. Schimek is a scholar working on Molecular Biology, Statistics and Probability and Artificial Intelligence. According to data from OpenAlex, Michael G. Schimek has authored 38 papers receiving a total of 761 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 8 papers in Statistics and Probability and 6 papers in Artificial Intelligence. Recurrent topics in Michael G. Schimek's work include Gene expression and cancer classification (7 papers), Bayesian Modeling and Causal Inference (4 papers) and Advanced Statistical Methods and Models (4 papers). Michael G. Schimek is often cited by papers focused on Gene expression and cancer classification (7 papers), Bayesian Modeling and Causal Inference (4 papers) and Advanced Statistical Methods and Models (4 papers). Michael G. Schimek collaborates with scholars based in Austria, United States and Germany. Michael G. Schimek's co-authors include Wolfgang Karl Härdle, Bastian Pfeifer, Thomas Frischer, Boštjan Gomišček, H. Puxbaum, Hanns Moshammer, Michael Kundi, Manfred Neuberger, Friedrich Horak and Andreas Holzinger and has published in prestigious journals such as Journal of the American Statistical Association, Blood and Bioinformatics.

In The Last Decade

Michael G. Schimek

36 papers receiving 729 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael G. Schimek Austria 16 181 103 101 69 57 38 761
Woojoo Lee South Korea 18 200 1.1× 91 0.9× 105 1.0× 62 0.9× 50 0.9× 123 1.2k
Sara López‐Pintado United States 15 191 1.1× 111 1.1× 388 3.8× 107 1.6× 45 0.8× 33 1.2k
Arnab Maity United States 19 248 1.4× 271 2.6× 358 3.5× 133 1.9× 70 1.2× 70 1.2k
Huann‐Sheng Chen United States 20 469 2.6× 34 0.3× 43 0.4× 50 0.7× 15 0.3× 51 1.4k
Ju‐Hyun Park South Korea 13 130 0.7× 110 1.1× 32 0.3× 44 0.6× 16 0.3× 65 935
Christopher M. Triggs New Zealand 22 305 1.7× 60 0.6× 50 0.5× 81 1.2× 5 0.1× 93 1.8k
Brian L. Joiner United States 14 79 0.4× 52 0.5× 249 2.5× 76 1.1× 31 0.5× 41 1.2k
Deepak K. Agarwal India 16 84 0.5× 314 3.0× 93 0.9× 82 1.2× 53 0.9× 29 1.1k
Eric Ziegel 10 97 0.5× 16 0.2× 135 1.3× 91 1.3× 20 0.4× 11 1.1k
Huajun Ye China 12 165 0.9× 74 0.7× 91 0.9× 39 0.6× 27 0.5× 31 538

Countries citing papers authored by Michael G. Schimek

Since Specialization
Citations

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

Fields of papers citing papers by Michael G. Schimek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael G. Schimek. 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 Michael G. Schimek. The network helps show where Michael G. Schimek may publish in the future.

Co-authorship network of co-authors of Michael G. Schimek

This figure shows the co-authorship network connecting the top 25 collaborators of Michael G. Schimek. A scholar is included among the top collaborators of Michael G. Schimek 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 Michael G. Schimek. Michael G. Schimek 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.
Schimek, Michael G., et al.. (2024). Correction to: Effective signal reconstruction from multiple ranked lists via convex optimization. Data Mining and Knowledge Discovery. 38(3). 1170–1170.
2.
Pfeifer, Bastian, Marcus Bloice, & Michael G. Schimek. (2023). Parea: Multi-view ensemble clustering for cancer subtype discovery. Journal of Biomedical Informatics. 143. 104406–104406. 11 indexed citations
3.
Pfeifer, Bastian, Nikolaos Alachiotis, Pavlos Pavlidis, & Michael G. Schimek. (2020). Genome scans for selection and introgression based on k ‐nearest neighbour techniques. Molecular Ecology Resources. 20(6). 1597–1609. 12 indexed citations
4.
Pfeifer, Bastian & Michael G. Schimek. (2020). A hierarchical clustering and data fusion approach for disease subtype discovery. Journal of Biomedical Informatics. 113. 103636–103636. 18 indexed citations
5.
Cvitic, Silvija, Boris Novakovic, Lavinia Gordon, et al.. (2018). Human fetoplacental arterial and venous endothelial cells are differentially programmed by gestational diabetes mellitus, resulting in cell-specific barrier function changes. Diabetologia. 61(11). 2398–2411. 41 indexed citations
6.
Schimek, Michael G., et al.. (2017). A novel method for estimating the common signals for consensus across multiple ranked lists. Computational Statistics & Data Analysis. 115. 122–135. 7 indexed citations
7.
Bettermann, Kira, Anita K. Mehta, Nicole Golob‐Schwarzl, et al.. (2016). Keratin 18-deficiency results in steatohepatitis and liver tumors in old mice: A model of steatohepatitis-associated liver carcinogenesis. Oncotarget. 7(45). 73309–73322. 19 indexed citations
8.
Mautner, Selma, Bernd Schultes, Thomas R. Pieber, et al.. (2016). An Untargeted Metabolomics Approach to Characterize Short-Term and Long-Term Metabolic Changes after Bariatric Surgery. PLoS ONE. 11(9). e0161425–e0161425. 51 indexed citations
9.
Schimek, Michael G., et al.. (2015). TopKLists: a comprehensive R package for statistical inference, stochastic aggregation, and visualization of multiple omics ranked lists. Statistical Applications in Genetics and Molecular Biology. 14(3). 311–6. 27 indexed citations
10.
Hall, Peter & Michael G. Schimek. (2012). Moderate-Deviation-Based Inference for Random Degeneration in Paired Rank Lists. Journal of the American Statistical Association. 107(498). 661–672. 17 indexed citations
11.
Blaschitz, Astrid, Martin Gauster, Dietmar Fuchs, et al.. (2011). Vascular Endothelial Expression of Indoleamine 2,3-Dioxygenase 1 Forms a Positive Gradient towards the Feto-Maternal Interface. PLoS ONE. 6(7). e21774–e21774. 55 indexed citations
12.
Ahammer, Helmut, Astrid Blaschitz, Angela Gismondi, et al.. (2011). A New Method for Morphometric Analysis of Tissue Distribution of Mobile Cells in Relation to Immobile Tissue Structures. PLoS ONE. 6(3). e15086–e15086. 4 indexed citations
13.
Schimek, Michael G.. (2009). Semiparametric penalized generalized additive models for environmental research and epidemiology. Environmetrics. 20(6). 699–717. 24 indexed citations
14.
Schimek, Michael G.. (2004). Penalized Binary Regression for Gene Expression Profiling. Methods of Information in Medicine. 43(5). 439–444. 5 indexed citations
15.
16.
Eubank, R. L., et al.. (1998). Estimation in partially linear models. Computational Statistics & Data Analysis. 29(1). 27–34. 39 indexed citations
17.
Schimek, Michael G.. (1997). Non- and Semiparametric Alternatives to Generalized Linear Models. SSRN Electronic Journal. 4 indexed citations
18.
19.
Schimek, Michael G., et al.. (1994). Dependent error regression smoothing: a new method and PC program. Computational Statistics & Data Analysis. 17(4). 457–464. 2 indexed citations
20.
Millner, Michael, et al.. (1989). Lyme borreliosis in children. European Journal of Pediatrics. 148(6). 527–530. 19 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Woojoo Lee Breakdown of academic impact, for papers by Sara López‐Pintado Breakdown of academic impact, for papers by Arnab Maity Breakdown of academic impact, for papers by Huann‐Sheng Chen Breakdown of academic impact, for papers by Ju‐Hyun Park Breakdown of academic impact, for papers by Christopher M. Triggs Breakdown of academic impact, for papers by Brian L. Joiner Breakdown of academic impact, for papers by Deepak K. Agarwal Breakdown of academic impact, for papers by Eric Ziegel Breakdown of academic impact, for papers by Huajun Ye
Rankless by CCL
2026