Matthias Hübenthal

3.4k total citations
16 papers, 351 citations indexed

About

Matthias Hübenthal is a scholar working on Dermatology, Molecular Biology and Genetics. According to data from OpenAlex, Matthias Hübenthal has authored 16 papers receiving a total of 351 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Dermatology, 5 papers in Molecular Biology and 5 papers in Genetics. Recurrent topics in Matthias Hübenthal's work include Dermatology and Skin Diseases (7 papers), Cancer-related molecular mechanisms research (4 papers) and MicroRNA in disease regulation (4 papers). Matthias Hübenthal is often cited by papers focused on Dermatology and Skin Diseases (7 papers), Cancer-related molecular mechanisms research (4 papers) and MicroRNA in disease regulation (4 papers). Matthias Hübenthal collaborates with scholars based in Germany, Lithuania and Norway. Matthias Hübenthal's co-authors include André Franke, Andreas Keller, Georg Hemmrich‐Stanisak, Simonas Juzėnas, Limas Kupčinskas, Marc P. Hoeppner, Maren Paulsen, Philip Rosenstiel, Martin Hofmann‐Apitius and Lars Wienbrandt and has published in prestigious journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Matthias Hübenthal

15 papers receiving 348 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthias Hübenthal Germany 9 197 173 46 45 42 16 351
Laura Nájera Spain 11 162 0.8× 60 0.3× 47 1.0× 27 0.6× 42 1.0× 29 329
Klára Prajzlerová Czechia 10 136 0.7× 83 0.5× 18 0.4× 23 0.5× 115 2.7× 23 406
Gabriel Skogberg Sweden 11 193 1.0× 70 0.4× 11 0.2× 33 0.7× 123 2.9× 13 350
Siming Gao China 11 157 0.8× 52 0.3× 19 0.4× 19 0.4× 87 2.1× 21 338
Hongmei Yi China 11 152 0.8× 55 0.3× 18 0.4× 20 0.4× 71 1.7× 39 423
Jan Kłos Norway 12 121 0.6× 145 0.8× 8 0.2× 31 0.7× 20 0.5× 19 441
Henning Weigt Germany 7 221 1.1× 158 0.9× 18 0.4× 13 0.3× 118 2.8× 10 434
Emily A. Merkel United States 11 145 0.7× 49 0.3× 89 1.9× 19 0.4× 53 1.3× 17 340
Jason Cosgrove United States 10 183 0.9× 29 0.2× 30 0.7× 41 0.9× 61 1.5× 17 349
Nam Kyu Lim South Korea 7 181 0.9× 78 0.5× 17 0.4× 13 0.3× 25 0.6× 29 332

Countries citing papers authored by Matthias Hübenthal

Since Specialization
Citations

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

Fields of papers citing papers by Matthias Hübenthal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthias Hübenthal

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

All Works

16 of 16 papers shown
1.
Meesters, Luca D., Janou A. Y. Roubroeks, Matthias Hübenthal, et al.. (2025). Dissecting key contributions of TH2 and TH17 cytokines to atopic dermatitis pathophysiology. Journal of Allergy and Clinical Immunology. 156(3). 690–704. 2 indexed citations
2.
Stölzl, Dora, Inken Harder, Elke Rodríguez, et al.. (2024). Stratum corneum and microbial biomarkers precede and characterize childhood atopic dermatitis. Journal of the European Academy of Dermatology and Venereology. 38(9). 1769–1775. 5 indexed citations
3.
Böhm, Ruwen, Henrike Bruckmueller, Stefan Oswald, et al.. (2024). Phenotype–Genotype Correlation Applying a Cocktail Approach and an Exome Chip Analysis Reveals Further Variants Contributing to Variation of Drug Metabolism. Clinical Pharmacology & Therapeutics. 116(1). 204–216. 1 indexed citations
4.
Emmert, Hila, Franziska Rademacher, Matthias Hübenthal, et al.. (2024). Type 2 Cytokine–Dependent Skin Barrier Regulation in Personalized 2-Dimensional and 3-Dimensional Skin Models of Atopic Dermatitis: A Pilot Study. SHILAP Revista de lepidopterología. 5(1). 100309–100309.
5.
Harder, Inken, Dora Stölzl, Matthias Hübenthal, et al.. (2024). Tralokinumab Treatment of Atopic Dermatitis Induces a Progressive Transcriptomic Response. Journal of Investigative Dermatology. 145(7). 1643–1652.e13. 2 indexed citations
6.
Möbus, Lena, Elke Rodríguez, Inken Harder, et al.. (2022). Blood transcriptome profiling identifies 2 candidate endotypes of atopic dermatitis. Journal of Allergy and Clinical Immunology. 150(2). 385–395. 33 indexed citations
7.
Carreras‐Badosa, Gemma, Julia Maslovskaja, Tarmo Annilo, et al.. (2022). miRNA expression profiles of the perilesional skin of atopic dermatitis and psoriasis patients are highly similar. Scientific Reports. 12(1). 22645–22645. 12 indexed citations
8.
Hübenthal, Matthias, Britt-Sabina Löscher, Jeanette Erdmann, et al.. (2021). Current Developments of Clinical Sequencing and the Clinical Utility of Polygenic Risk Scores in Inflammatory Diseases. Frontiers in Immunology. 11. 577677–577677. 6 indexed citations
9.
Jung, Eun Suk, Seung Won Kim, Matthias Hübenthal, et al.. (2019). ZNF133 is associated with infliximab responsiveness in patients with inflammatory bowel diseases. Journal of Gastroenterology and Hepatology. 34(10). 1727–1735. 8 indexed citations
10.
Wienbrandt, Lars, Jan Christian Kässens, Matthias Hübenthal, & David Ellinghaus. (2018). 1000× faster than PLINK: Combined FPGA and GPU accelerators for logistic regression-based detection of epistasis. Journal of Computational Science. 30. 183–193. 18 indexed citations
11.
Fehlmann, Tobias, Christina Backes, Jan Haas, et al.. (2017). Web-based NGS data analysis using miRMaster: a large-scale meta-analysis of human miRNAs. Nucleic Acids Research. 45(15). 8731–8744. 50 indexed citations
12.
Juzėnas, Simonas, Matthias Hübenthal, Marc P. Hoeppner, et al.. (2017). A comprehensive, cell specific microRNA catalogue of human peripheral blood. Nucleic Acids Research. 45(16). 9290–9301. 120 indexed citations
13.
Juzėnas, Simonas, Juozas Kupčinskas, Lina Poškienė, et al.. (2017). MiRNA profiling of gastrointestinal stromal tumors by next-generation sequencing. Oncotarget. 8(23). 37225–37238. 29 indexed citations
14.
Wienbrandt, Lars, Jan Christian Kässens, Matthias Hübenthal, & David Ellinghaus. (2017). Fast Genome-Wide Third-order SNP Interaction Tests with Information Gain on a Low-cost Heterogeneous Parallel FPGA-GPU Computing Architecture. Procedia Computer Science. 108. 596–605. 12 indexed citations
15.
Fehlmann, Tobias, Christina Backes, Julia Alles, et al.. (2017). A high-resolution map of the human small non-coding transcriptome. Bioinformatics. 34(10). 1621–1628. 19 indexed citations
16.
Hübenthal, Matthias, Georg Hemmrich‐Stanisak, Frauke Degenhardt, et al.. (2015). Sparse Modeling Reveals miRNA Signatures for Diagnostics of Inflammatory Bowel Disease. PLoS ONE. 10(10). e0140155–e0140155. 34 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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