Johannes Raffler

5.3k total citations
20 papers, 838 citations indexed

About

Johannes Raffler is a scholar working on Molecular Biology, Epidemiology and Genetics. According to data from OpenAlex, Johannes Raffler has authored 20 papers receiving a total of 838 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 4 papers in Epidemiology and 4 papers in Genetics. Recurrent topics in Johannes Raffler's work include Metabolomics and Mass Spectrometry Studies (8 papers), Bioinformatics and Genomic Networks (5 papers) and Genetic Associations and Epidemiology (4 papers). Johannes Raffler is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (8 papers), Bioinformatics and Genomic Networks (5 papers) and Genetic Associations and Epidemiology (4 papers). Johannes Raffler collaborates with scholars based in Germany, Qatar and United States. Johannes Raffler's co-authors include Gabi Kastenmüller, Karsten Suhre, Matthias Arnold, Arne Pfeufer, Christian Gieger, Claudia Langenberg, Isobel D. Stewart, Maik Pietzner, Nicholas J. Wareham and Gregory Michelotti and has published in prestigious journals such as Nature Medicine, Nature Communications and Bioinformatics.

In The Last Decade

Johannes Raffler

17 papers receiving 835 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Johannes Raffler Germany 12 496 253 148 104 52 20 838
Yingying Luo China 21 500 1.0× 329 1.3× 228 1.5× 180 1.7× 46 0.9× 74 1.5k
Niina Sandholm Finland 20 327 0.7× 248 1.0× 128 0.9× 170 1.6× 39 0.8× 57 1.1k
Mengyin Cai China 15 399 0.8× 229 0.9× 212 1.4× 199 1.9× 58 1.1× 43 1.1k
Andreas Peter Germany 21 493 1.0× 124 0.5× 195 1.3× 144 1.4× 95 1.8× 85 1.3k
Tarunveer S. Ahluwalia Denmark 22 419 0.8× 277 1.1× 361 2.4× 193 1.9× 54 1.0× 56 1.4k
Adán Valladares‐Salgado Mexico 16 222 0.4× 164 0.6× 112 0.8× 100 1.0× 58 1.1× 50 717
Chang Ho Ahn South Korea 19 328 0.7× 132 0.5× 117 0.8× 122 1.2× 61 1.2× 96 1.1k
Sabina Semiz Bosnia and Herzegovina 19 526 1.1× 97 0.4× 180 1.2× 128 1.2× 44 0.8× 42 1.0k
Rebecca L. Pollex Canada 23 436 0.9× 341 1.3× 153 1.0× 224 2.2× 152 2.9× 33 1.4k
Anna Perri Italy 19 440 0.9× 157 0.6× 65 0.4× 157 1.5× 60 1.2× 73 1.2k

Countries citing papers authored by Johannes Raffler

Since Specialization
Citations

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

Fields of papers citing papers by Johannes Raffler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Johannes Raffler

This figure shows the co-authorship network connecting the top 25 collaborators of Johannes Raffler. A scholar is included among the top collaborators of Johannes Raffler 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 Johannes Raffler. Johannes Raffler 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.
Meyer, Philip, Dominik Müller, Anna Muzalyova, et al.. (2025). Do explainable AI (XAI) methods improve the acceptance of AI in clinical practice? An evaluation of XAI methods on Gleason grading. The Journal of Pathology Clinical Research. 11(2). e70023–e70023.
2.
3.
Raffler, Johannes, Werner Römisch‐Margl, Matthias Arnold, et al.. (2024). The HuMet Repository: Watching human metabolism at work. Cell Reports. 43(8). 114416–114416. 1 indexed citations
4.
Meyer, Philip, Bruno Märkl, Ralf Huss, et al.. (2024). Assessing the Performance of Deep Learning for Automated Gleason Grading in Prostate Cancer. Studies in health technology and informatics. 316. 1110–1114. 2 indexed citations
5.
Huss, Ralf, Johannes Raffler, & Bruno Märkl. (2023). Artificial intelligence and digital biomarker in precision pathology guiding immune therapy selection and precision oncology. Cancer Reports. 6(7). e1796–e1796. 7 indexed citations
6.
Fiamoncini, Jarlei, Daniela Schranner, Johannes Raffler, et al.. (2022). Dynamic patterns of postprandial metabolic responses to three dietary challenges. Frontiers in Nutrition. 9. 933526–933526. 5 indexed citations
7.
Pietzner, Maik, Eleanor Wheeler, Julia Carrasco-Zanini, et al.. (2021). Author Correction: Genetic architecture of host proteins involved in SARS-CoV-2 infection. Nature Communications. 12(1). 845–845.
8.
Pietzner, Maik, Isobel D. Stewart, Johannes Raffler, et al.. (2021). Plasma metabolites to profile pathways in noncommunicable disease multimorbidity. Nature Medicine. 27(3). 471–479. 129 indexed citations
9.
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
10.
Pietzner, Maik, Eleanor Wheeler, Julia Carrasco-Zanini, et al.. (2020). Genetic architecture of host proteins involved in SARS-CoV-2 infection. Nature Communications. 11(1). 6397–6397. 69 indexed citations
11.
Köttgen, Anna, Johannes Raffler, Peggy Sekula, & Gabi Kastenmüller. (2018). Genome-Wide Association Studies of Metabolite Concentrations (mGWAS): Relevance for Nephrology. Seminars in Nephrology. 38(2). 151–174. 21 indexed citations
12.
Trinh, Kieu, Simone Wahl, Johannes Raffler, et al.. (2018). Characterization of missing values in untargeted MS-based metabolomics data and evaluation of missing data handling strategies. Metabolomics. 14(10). 128–128. 123 indexed citations
13.
Naveja, J. Jesús, et al.. (2018). HitPickV2: a web server to predict targets of chemical compounds. Bioinformatics. 35(7). 1239–1240. 26 indexed citations
14.
Rueedi, Rico, Roger Mallol, Johannes Raffler, et al.. (2017). Metabomatching: Using genetic association to identify metabolites in proton NMR spectroscopy. PLoS Computational Biology. 13(12). e1005839–e1005839. 13 indexed citations
15.
Kim, Hye In, Johannes Raffler, Wenyun Lu, et al.. (2017). Fine Mapping and Functional Analysis Reveal a Role of SLC22A1 in Acylcarnitine Transport. The American Journal of Human Genetics. 101(4). 489–502. 48 indexed citations
16.
Suhre, Karsten, Johannes Raffler, & Gabi Kastenmüller. (2015). Biochemical insights from population studies with genetics and metabolomics. Archives of Biochemistry and Biophysics. 589. 168–176. 40 indexed citations
17.
Kastenmüller, Gabi, Johannes Raffler, Christian Gieger, & Karsten Suhre. (2015). Genetics of human metabolism: an update. Human Molecular Genetics. 24(R1). R93–R101. 87 indexed citations
18.
Raffler, Johannes, Nele Friedrich, Matthias Arnold, et al.. (2015). Genome-Wide Association Study with Targeted and Non-targeted NMR Metabolomics Identifies 15 Novel Loci of Urinary Human Metabolic Individuality. PLoS Genetics. 11(9). e1005487–e1005487. 61 indexed citations
19.
Arnold, Matthias, Johannes Raffler, Arne Pfeufer, Karsten Suhre, & Gabi Kastenmüller. (2014). SNiPA: an interactive, genetic variant-centered annotation browser. Bioinformatics. 31(8). 1334–1336. 179 indexed citations
20.
Raffler, Johannes, Werner Römisch‐Margl, Ann-Kristin Petersen, et al.. (2013). Identification and MS-assisted interpretation of genetically influenced NMR signals in human plasma. Genome Medicine. 5(2). 13–13. 17 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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