Dietrich Mäde

909 total citations
37 papers, 728 citations indexed

About

Dietrich Mäde is a scholar working on Food Science, Infectious Diseases and Molecular Biology. According to data from OpenAlex, Dietrich Mäde has authored 37 papers receiving a total of 728 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Food Science, 13 papers in Infectious Diseases and 12 papers in Molecular Biology. Recurrent topics in Dietrich Mäde's work include Viral gastroenteritis research and epidemiology (12 papers), Salmonella and Campylobacter epidemiology (10 papers) and Genetically Modified Organisms Research (7 papers). Dietrich Mäde is often cited by papers focused on Viral gastroenteritis research and epidemiology (12 papers), Salmonella and Campylobacter epidemiology (10 papers) and Genetically Modified Organisms Research (7 papers). Dietrich Mäde collaborates with scholars based in Germany, Switzerland and Ireland. Dietrich Mäde's co-authors include Reimar Johne, Lutz Grohmann, Marina Höhne, Dirk W. Höper, Eckhard Strauch, Lüppo Ellerbroek, Kirsten Simon, Joanna Ollivier, Saskia A. Rutjes and James Lowther and has published in prestigious journals such as Journal of Clinical Microbiology, International Journal of Food Microbiology and Journal of Applied Microbiology.

In The Last Decade

Dietrich Mäde

37 papers receiving 696 citations

Peers

Dietrich Mäde

GENET

Adam Allred United States

Cheng Tang China

Marina Mozgovoj Argentina

Erin DiCaprio United States

Leslie A. Dauphin United States

Tammy Bui United States

Yuanmei Ma United States

Pornphan Diraphat Thailand

Edward D. McGruder United States

Adam Allred United States

Dietrich Mäde

242 ×0.7

125 ×0.6

95 ×0.7

70 ×0.5

GENET

34 ×0.3

Citations per year, relative to Dietrich Mäde Dietrich Mäde (= 1×) peers Adam Allred

Countries citing papers authored by Dietrich Mäde

Since Specialization

Citations

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

Fields of papers citing papers by Dietrich Mäde

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dietrich Mäde

This figure shows the co-authorship network connecting the top 25 collaborators of Dietrich Mäde. A scholar is included among the top collaborators of Dietrich Mäde 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 Dietrich Mäde. Dietrich Mäde 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

Zautner, Andreas E., et al.. (2022). Human Erysipelothrix rhusiopathiae infection via bath water – case report and genome announcement. Frontiers in Cellular and Infection Microbiology. 12. 981477–981477. 5 indexed citations

Trojnar, E., Matthias Contzen, Jochen Kilwinski, et al.. (2020). Interlaboratory Validation of a Detection Method for Hepatitis E Virus RNA in Pig Liver. Microorganisms. 8(10). 1460–1460. 3 indexed citations

Höper, Dirk W., et al.. (2018). Analysis of frozen strawberries involved in a large norovirus gastroenteritis outbreak using next generation sequencing and digital PCR. Food Microbiology. 76. 390–395. 43 indexed citations

Althof, Nadine, E. Trojnar, Thomas Böhm, et al.. (2018). Interlaboratory Validation of a Method for Hepatitis E Virus RNA Detection in Meat and Meat Products. Food and Environmental Virology. 11(1). 1–8. 17 indexed citations

Waiblinger, Hans‐Ulrich, et al.. (2018). Official food control laboratories in Germany: results of GMO analyses from 2012 to 2016. Journal of Consumer Protection and Food Safety. 13(2). 139–144. 1 indexed citations

Lowther, James, Albert Bosch, Sophie Butot, et al.. (2017). Validation of EN ISO method 15216 - Part 1 – Quantification of hepatitis A virus and norovirus in food matrices. International Journal of Food Microbiology. 288. 82–90. 86 indexed citations

Ehlers, Bernhard, et al.. (2016). Detection and genome characterization of bovine polyomaviruses in beef muscle and ground beef samples from Germany. International Journal of Food Microbiology. 241. 168–172. 10 indexed citations

Uhlig, Steffen, et al.. (2015). Validation of qualitative PCR methods on the basis of mathematical–statistical modelling of the probability of detection. Accreditation and Quality Assurance. 20(2). 75–83. 52 indexed citations

Grohmann, Lutz, et al.. (2013). Detection and characterization of an unknown rice event in Basmati rice products. European Food Research and Technology. 236(4). 715–723. 8 indexed citations

10.

Mäde, Dietrich, et al.. (2013). Detection and Typing of Norovirus from Frozen Strawberries Involved in a Large-Scale Gastroenteritis Outbreak in Germany. Food and Environmental Virology. 5(3). 162–168. 124 indexed citations

11.

Malorny, Burkhard, Dietrich Mäde, & Charlotta Löfström. (2013). Real-time PCR Detection of Food-borne Pathogenic Salmonella spp.. 57–78. 3 indexed citations

12.

Kraushaar, Britta, et al.. (2011). Characterization of a Yersinia enterocolitica biotype 1A strain harbouring an ail gene. Journal of Applied Microbiology. 111(4). 997–1005. 37 indexed citations

13.

Grohmann, Lutz, et al.. (2010). A testing cascade for the detection of genetically modified rice by real-time PCR in food and its application for detection of an unauthorized rice line similar to KeFeng6. Journal of Consumer Protection and Food Safety. 5(2). 185–188. 16 indexed citations

14.

Grohmann, Lutz & Dietrich Mäde. (2008). Detection of genetically modified rice: collaborative validation study of a construct-specific real-time PCR method for detection of transgenic Bt rice. European Food Research and Technology. 228(3). 497–500. 14 indexed citations

15.

Malorny, Burkhard, et al.. (2007). Multicenter validation study of two blockcycler- and one capillary-based real-time PCR methods for the detection of Salmonella in milk powder. International Journal of Food Microbiology. 117(2). 211–218. 37 indexed citations

16.

Mäde, Dietrich, et al.. (2007). Molekularbiologischer Nachweis von Viren in Lebensmitteln. Journal of Consumer Protection and Food Safety. 2(2). 230–238. 1 indexed citations

17.

Mäde, Dietrich, J Dreier, Martina Hagen, et al.. (2006). Nachweis von Noroviren in Umgebungsproben. Ergebnisse eines Ringversuchs zur Methodenentwicklung. OpenAgrar. 2 indexed citations

18.

Mäde, Dietrich, et al.. (2000). Detection of Clostridium botulinum in honey by polymerase chain reaction. Archiv für Lebensmittelhygiene. 51(3). 68–70. 5 indexed citations

19.

Hertel, Christian, et al.. (1999). Development and application of a heterologous internal standard for polymerase-chain-reaction-based detection of Campylobacter jejuni and Campylobacter coli in foods. European Food Research and Technology. 209(3-4). 180–184. 6 indexed citations

20.

Mäde, Dietrich, et al.. (1996). [Investigations of raw milk for Shiga-like toxin producing Escherichia coli by the polymerase chain reaction].. PubMed. 103(12). 511–2. 3 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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