Karsten Suhre

34.0k total citations · 4 hit papers
285 papers, 13.2k citations indexed

About

Karsten Suhre is a scholar working on Molecular Biology, Genetics and Physiology. According to data from OpenAlex, Karsten Suhre has authored 285 papers receiving a total of 13.2k indexed citations (citations by other indexed papers that have themselves been cited), including 173 papers in Molecular Biology, 71 papers in Genetics and 47 papers in Physiology. Recurrent topics in Karsten Suhre's work include Metabolomics and Mass Spectrometry Studies (92 papers), Bioinformatics and Genomic Networks (39 papers) and Genetic Associations and Epidemiology (35 papers). Karsten Suhre is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (92 papers), Bioinformatics and Genomic Networks (39 papers) and Genetic Associations and Epidemiology (35 papers). Karsten Suhre collaborates with scholars based in Qatar, Germany and United States. Karsten Suhre's co-authors include Jerzy Adamski, Christian Gieger, Yves‐Henri Sanejouand, Gabi Kastenmüller, Thomas Illig, Jean‐Michel Claverie, Werner Römisch‐Margl, Elisabeth Altmaier, Cornelia Prehn and Jan Krumsiek and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Karsten Suhre

276 papers receiving 13.0k 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.

ElNemo: a normal mode web server for protein movement analysis and the generation of templates for molecular replacement

2004 576 citations Karsten Suhre et al. Nucleic Acids Research profile →
A genome-wide perspective of genetic variation in human metabolism

2009 475 citations Christian Gieger, Werner Römisch‐Margl et al. profile →
Metabolomics enables precision medicine: “A White Paper, Community Perspective”

2016 417 citations Karsten Suhre, Gabi Kastenmüller et al. profile →
Genetics meets proteomics: perspectives for large population-based studies

2020 223 citations Karsten Suhre et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Karsten Suhre Qatar	64	8.1k	2.4k	2.3k	1.3k	940	285	13.2k
Jian Li China	66	7.2k 0.9×	1.4k 0.6×	846 0.4×	1.0k 0.8×	1.2k 1.3×	891	19.2k
S P H Alexander United Kingdom	70	9.9k 1.2×	3.3k 1.4×	847 0.4×	1.2k 0.9×	571 0.6×	244	23.2k
Richard A. Anderson United States	70	8.6k 1.1×	2.0k 0.8×	1.1k 0.5×	783 0.6×	538 0.6×	290	15.8k
Jianjun Liu China	64	7.1k 0.9×	2.1k 0.9×	3.0k 1.3×	1.7k 1.4×	2.7k 2.9×	1.1k	20.1k
J. David Lambeth United States	81	11.5k 1.4×	8.4k 3.5×	1.1k 0.5×	895 0.7×	1.3k 1.4×	184	25.1k
Hiroshi Hara Japan	55	5.1k 0.6×	1.9k 0.8×	2.0k 0.9×	796 0.6×	240 0.3×	726	14.1k
Koen Venema Netherlands	59	10.0k 1.2×	4.4k 1.8×	1.6k 0.7×	1.2k 0.9×	194 0.2×	288	17.4k
A. Ian Smith Australia	61	5.0k 0.6×	1.0k 0.4×	1.1k 0.5×	641 0.5×	566 0.6×	333	14.1k
Wenyun Lu United States	51	6.4k 0.8×	1.3k 0.5×	679 0.3×	1.5k 1.1×	1.7k 1.8×	120	10.5k
Gerd Schmitz Germany	91	14.4k 1.8×	3.9k 1.6×	1.8k 0.8×	3.7k 2.9×	3.3k 3.5×	661	32.1k

Countries citing papers authored by Karsten Suhre

Since Specialization

Citations

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

Fields of papers citing papers by Karsten Suhre

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Karsten Suhre

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

All Works

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20 of 20 papers shown

Visconti, Alessia, Niccolò Rossi, Albert Bondt, et al.. (2024). The genetics and epidemiology of N- and O-immunoglobulin A glycomics. Genome Medicine. 16(1). 96–96. 2 indexed citations

Batra, Richa, et al.. (2024). AutoFocus: a hierarchical framework to explore multi-omic disease associations spanning multiple scales of biomolecular interaction. Communications Biology. 7(1). 1094–1094. 1 indexed citations

Shi, Mengya, Karsten Suhre, Cornelia Prehn, et al.. (2024). Omentin associates with serum metabolite profiles indicating lower diabetes risk: KORA F4 Study. BMJ Open Diabetes Research & Care. 12(2). e003865–e003865.

Maalmi, Haïfa, Holger Prokisch, Barbara Thorand, et al.. (2024). Interpretable multimodal machine learning (IMML) framework reveals pathological signatures of distal sensorimotor polyneuropathy. SHILAP Revista de lepidopterología. 4(1). 265–265.

Sun, Benjamin B., Karsten Suhre, & Bradford W. Gibson. (2024). Promises and Challenges of populational Proteomics in Health and Disease. Molecular & Cellular Proteomics. 23(7). 100786–100786. 15 indexed citations

Halama, Anna, et al.. (2023). Characterization of exercise-induced hemolysis in endurance horses. Frontiers in Veterinary Science. 10. 1115776–1115776. 3 indexed citations

Batra, Richa, Oleh M. Akchurin, Sergio Alvarez-Mulett, et al.. (2023). Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS. Molecular Medicine. 29(1). 13–13. 12 indexed citations

Büyüközkan, Mustafa, Karsten Suhre, & Jan Krumsiek. (2021). SGI: automatic clinical subgroup identification in omics datasets. Bioinformatics. 38(2). 573–576. 1 indexed citations

Aguiar‐Pulido, Vanessa, Alexander Martinez‐Fundichely, Eran Elhaik, et al.. (2021). Systems biology analysis of human genomes points to key pathways conferring spina bifida risk. Proceedings of the National Academy of Sciences. 118(51). 10 indexed citations

10.

Madani, Aisha Y., Yasser Majeed, Houari Abdesselem, et al.. (2021). Signal Transducer and Activator of Transcription 3 (STAT3) Suppresses STAT1/Interferon Signaling Pathway and Inflammation in Senescent Preadipocytes. Antioxidants. 10(2). 334–334. 26 indexed citations

11.

Nag, Abhishek, Yuko Kurushima, Ruth C. E. Bowyer, et al.. (2020). Genome-wide scan identifies novel genetic loci regulating salivary metabolite levels. Human Molecular Genetics. 29(5). 864–875. 10 indexed citations

12.

Elhadad, Mohamed A., Christian Jonasson, Cornelia Huth, et al.. (2020). Deciphering the Plasma Proteome of Type 2 Diabetes. Diabetes. 69(12). 2766–2778. 36 indexed citations

13.

Verma, Akanksha, Thangamani Muthukumar, Hua Yang, et al.. (2020). Urinary cell transcriptomics and acute rejection in human kidney allografts. JCI Insight. 5(4). 25 indexed citations

14.

Scherer, Dominique, Hermann Brenner, Mélanie Waldenberger, et al.. (2020). Robust Huber-LASSO for improved prediction of protein, metabolite and gene expression levels relying on individual genotype data. Briefings in Bioinformatics. 22(4). 10 indexed citations

15.

Benedetti, Elisa, Maja Pučić‐Baković, Toma Keser, et al.. (2020). A strategy to incorporate prior knowledge into correlation network cutoff selection. Nature Communications. 11(1). 5153–5153. 17 indexed citations

16.

Trinh, Kieu, et al.. (2018). MoDentify : phenotype-driven module identification in metabolomics networks at different resolutions. Bioinformatics. 35(3). 532–534. 13 indexed citations

17.

Stacey, David, Eric B. Fauman, Daniel Ziemek, et al.. (2018). ProGeM: a framework for the prioritization of candidate causal genes at molecular quantitative trait loci. Nucleic Acids Research. 47(1). e3–e3. 57 indexed citations

18.

Sekula, Peggy, Katja Dettmer, Wolfram Gronwald, et al.. (2017). From Discovery to Translation: Characterization of C-Mannosyltryptophan and Pseudouridine as Markers of Kidney Function. Scientific Reports. 7(1). 17400–17400. 26 indexed citations

19.

Kumar, Pankaj, Anna Halama, Shahina Hayat, et al.. (2015). MetaRNA-Seq: An Interactive Tool to Browse and Annotate Metadata from RNA-Seq Studies. BioMed Research International. 2015. 1–6. 4 indexed citations

20.

Renner, Simone, Werner Römisch‐Margl, Cornelia Prehn, et al.. (2012). Changing Metabolic Signatures of Amino Acids and Lipids During the Prediabetic Period in a Pig Model With Impaired Incretin Function and Reduced β-Cell Mass. Diabetes. 61(8). 2166–2175. 39 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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