David Stadler

1.6k total citations · 1 hit paper
52 papers, 1.2k citations indexed

About

David Stadler is a scholar working on Molecular Biology, Renewable Energy, Sustainability and the Environment and Food Science. According to data from OpenAlex, David Stadler has authored 52 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 9 papers in Renewable Energy, Sustainability and the Environment and 6 papers in Food Science. Recurrent topics in David Stadler's work include Protist diversity and phylogeny (14 papers), Photosynthetic Processes and Mechanisms (12 papers) and Fungal and yeast genetics research (8 papers). David Stadler is often cited by papers focused on Protist diversity and phylogeny (14 papers), Photosynthetic Processes and Mechanisms (12 papers) and Fungal and yeast genetics research (8 papers). David Stadler collaborates with scholars based in United States, Austria and Germany. David Stadler's co-authors include Rudolf Krska, Michael Sulyok, David J Steiner, Franz Berthiller, Beverly Kariya, Laura Serna, Janos Groh, Rainer Schuhmacher, David A. Smith and Rudolf Martini and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Physics Today.

In The Last Decade

David Stadler

51 papers receiving 1.1k citations

Hit Papers

Validation of an LC-MS/MS-based dilute-and-shoot approach... 2020 2026 2022 2024 2020 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Stadler United States 23 648 515 198 108 95 52 1.2k
Rob J. Aerts Netherlands 18 795 1.2× 630 1.2× 197 1.0× 88 0.8× 255 2.7× 25 1.6k
J. G. Lafontaine Canada 21 836 1.3× 706 1.4× 212 1.1× 28 0.3× 70 0.7× 58 1.4k
D. J. Morr� United States 20 1.0k 1.6× 622 1.2× 280 1.4× 58 0.5× 115 1.2× 61 1.5k
Helga Ninnemann Germany 22 784 1.2× 848 1.6× 97 0.5× 88 0.8× 128 1.3× 52 1.4k
Dorothy Newmeyer United States 16 1.3k 2.0× 484 0.9× 275 1.4× 30 0.3× 86 0.9× 22 1.6k
Eugene L. Vigil United States 15 576 0.9× 467 0.9× 164 0.8× 47 0.4× 79 0.8× 36 934
J. Reinert Germany 19 1.3k 2.0× 1.0k 2.0× 151 0.8× 69 0.6× 85 0.9× 62 1.5k
Bert van Duijn Netherlands 25 1.0k 1.5× 988 1.9× 179 0.9× 48 0.4× 92 1.0× 67 1.8k
Mona C. Mehdy United States 19 1.1k 1.7× 1.2k 2.4× 792 4.0× 53 0.5× 157 1.7× 24 2.3k
Shoshi Muto Japan 33 1.5k 2.3× 2.0k 4.0× 234 1.2× 55 0.5× 111 1.2× 83 2.9k

Countries citing papers authored by David Stadler

Since Specialization
Citations

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

Fields of papers citing papers by David Stadler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Stadler

This figure shows the co-authorship network connecting the top 25 collaborators of David Stadler. A scholar is included among the top collaborators of David Stadler 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 David Stadler. David Stadler 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.
Steiner, Beate, et al.. (2024). Enzymatic detection of α-hydroxybutyrate, an important marker of insulin resistance, and comparison with LC-MS/MS detection. Practical Laboratory Medicine. 40. e00398–e00398. 4 indexed citations
2.
Stadler, David, Konrad Knöpper, Panagiota Arampatzi, et al.. (2023). Cytotoxic CNS-associated T cells drive axon degeneration by targeting perturbed oligodendrocytes in PLP1 mutant mice. iScience. 26(5). 106698–106698. 5 indexed citations
3.
Günthner, Roman, Lukas Streese, Susanne Angermann, et al.. (2022). Mortality prediction of retinal vessel diameters and function in a long-term follow-up of haemodialysis patients. Cardiovascular Research. 118(16). 3239–3249. 6 indexed citations
4.
Sulyok, Michael, David Stadler, David J Steiner, & Rudolf Krska. (2020). Validation of an LC-MS/MS-based dilute-and-shoot approach for the quantification of > 500 mycotoxins and other secondary metabolites in food crops: challenges and solutions. Analytical and Bioanalytical Chemistry. 412(11). 2607–2620. 194 indexed citations breakdown →
5.
Stadler, David, Franz Berthiller, Michele Suman, Rainer Schuhmacher, & Rudolf Krska. (2019). Novel analytical methods to study the fate of mycotoxins during thermal food processing. Analytical and Bioanalytical Chemistry. 412(1). 9–16. 40 indexed citations
6.
Stadler, David, Francesca Lambertini, Christoph Bueschl, et al.. (2018). Untargeted LC–MS based 13C labelling provides a full mass balance of deoxynivalenol and its degradation products formed during baking of crackers, biscuits and bread. Food Chemistry. 279. 303–311. 29 indexed citations
7.
Groh, Janos, et al.. (2016). Sialoadhesin promotes neuroinflammation‐related disease progression in two mouse models of CLN disease. Glia. 64(5). 792–809. 41 indexed citations
8.
Groh, Janos, Hana Friedman, Nadiya Orel, et al.. (2016). Pathogenicinflammation in the CNS of mice carrying humanPLP1mutations. Human Molecular Genetics. 25(21). ddw296–ddw296. 22 indexed citations
9.
Dillon, Davin C. & David Stadler. (1994). Spontaneous mutation at the mtr locus in neurospora: the molecular spectrum in wild-type and a mutator strain.. Genetics. 138(1). 61–74. 13 indexed citations
10.
Stadler, David, et al.. (1987). Repair-Resistant Mutation in Neurospora. Genetics. 116(2). 207–214. 3 indexed citations
11.
Stadler, David, et al.. (1984). A dose-rate effect in UV mutagenesis in Neurospora. Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis. 127(1). 39–47. 5 indexed citations
12.
Stadler, David. (1983). Repair and mutation following UV damage in heterokaryons of Neurospora. Molecular and General Genetics MGG. 190(2). 227–232. 8 indexed citations
13.
Stadler, David & Beverly Kariya. (1973). MARKER EFFECTS IN THE GENETIC TRANSDUCTION OF TRYPTOPHAN MUTANTS OF E. COLI. Genetics. 75(3). 423–439. 11 indexed citations
14.
Stadler, David & David A. Smith. (1968). A NEW MUTATION INNEUROSPORAFOR SENSITIVITY TO ULTRAVIOLET. Canadian Journal of Genetics and Cytology. 10(4). 916–919. 33 indexed citations
15.
Stadler, David. (1967). SUPPRESSORS OF AMINO ACID UPTAKE MUTANTS OF NEUROSPORA. Genetics. 57(4). 935–942. 10 indexed citations
16.
Fincham, J. R. S. & David Stadler. (1965). Complementation relationships ofNeurospora ammutants in relation to their formation of abnormal varieties of glutamate dehydrogenase. Genetics Research. 6(1). 121–129. 22 indexed citations
17.
Stadler, David. (1956). DOUBLE CROSSING OVER IN NEUROSPORA. Genetics. 41(4). 623–630. 14 indexed citations
18.
Stadler, David. (1956). A MAP OF LINKAGE GROUP VI OF NEUROSPORA CRASSA. Genetics. 41(4). 528–543. 38 indexed citations
19.
Stadler, David. (1953). CHEMOTROPISM IN RHIZOPUS NIGRICANS. II. THE ACTION OF PLANT JUICES. Biological Bulletin. 104(1). 100–108. 3 indexed citations
20.
Stadler, David. (1952). Chemotropism in Rhizopus nigricans: The staling reaction. Journal of Cellular and Comparative Physiology. 39(3). 449–474. 27 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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