Stephan Kamrad

954 total citations
20 papers, 527 citations indexed

About

Stephan Kamrad is a scholar working on Molecular Biology, Biochemistry and Genetics. According to data from OpenAlex, Stephan Kamrad has authored 20 papers receiving a total of 527 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 4 papers in Biochemistry and 2 papers in Genetics. Recurrent topics in Stephan Kamrad's work include Bioinformatics and Genomic Networks (10 papers), Microbial Metabolic Engineering and Bioproduction (7 papers) and Fungal and yeast genetics research (6 papers). Stephan Kamrad is often cited by papers focused on Bioinformatics and Genomic Networks (10 papers), Microbial Metabolic Engineering and Bioproduction (7 papers) and Fungal and yeast genetics research (6 papers). Stephan Kamrad collaborates with scholars based in United Kingdom, Germany and Sweden. Stephan Kamrad's co-authors include Markus Ralser, Jürg Bähler, Robert Haas, Aleksej Zelezniak, Michael Mülleder, StJohn Townsend, Clara Correia‐Melo, Jacopo Iacovacci, Jakob Vowinckel and Maria Rodríguez‐López and has published in prestigious journals such as Nature, Cell and eLife.

In The Last Decade

Stephan Kamrad

18 papers receiving 520 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stephan Kamrad United Kingdom 11 430 41 38 34 34 20 527
Nadine Dyballa‐Rukes Germany 9 260 0.6× 18 0.4× 25 0.7× 41 1.2× 62 1.8× 14 475
Lucía Herrera-Domínguez United Kingdom 10 440 1.0× 38 0.9× 14 0.4× 58 1.7× 35 1.0× 10 598
Venkata Chandrasekhar Nainala United Kingdom 4 507 1.2× 66 1.6× 108 2.8× 19 0.6× 58 1.7× 4 662
Hamid Baniasadi United States 9 272 0.6× 25 0.6× 36 0.9× 13 0.4× 28 0.8× 16 350
Jolanda van Leeuwen Netherlands 17 451 1.0× 33 0.8× 10 0.3× 22 0.6× 87 2.6× 29 836
Ulf W. Liebal Germany 10 314 0.7× 101 2.5× 78 2.1× 19 0.6× 15 0.4× 20 407
David Wildridge United Kingdom 8 318 0.7× 26 0.6× 92 2.4× 11 0.3× 31 0.9× 8 466
Nils Christian Germany 10 378 0.9× 86 2.1× 29 0.8× 13 0.4× 72 2.1× 13 479
Helen J. Tweeddale Australia 7 331 0.8× 33 0.8× 78 2.1× 19 0.6× 28 0.8× 10 411
Wenhua Tong China 9 192 0.4× 57 1.4× 8 0.2× 91 2.7× 35 1.0× 21 402

Countries citing papers authored by Stephan Kamrad

Since Specialization
Citations

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

Fields of papers citing papers by Stephan Kamrad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stephan Kamrad

This figure shows the co-authorship network connecting the top 25 collaborators of Stephan Kamrad. A scholar is included among the top collaborators of Stephan Kamrad 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 Stephan Kamrad. Stephan Kamrad 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.
Smith, Tom, Shagun Krishna, Rui Guan, et al.. (2025). Industrial and agricultural chemicals exhibit antimicrobial activity against human gut bacteria in vitro. Nature Microbiology. 10(12). 3107–3121.
2.
Aulakh, Simran Kaur, Oliver Lemke, Łukasz Szyrwiel, et al.. (2025). The molecular landscape of cellular metal ion biology. Cell Systems. 16(7). 101319–101319. 3 indexed citations
3.
Kamrad, Stephan, Teresa A. Davis, & Kiran Raosaheb Patil. (2025). Impact of drugs and environmental contaminants on amine production by gut bacteria. Molecular Systems Biology. 21(10). 1351–1370.
4.
Rodríguez‐López, Maria, Nicola Bordin, Jonathan Lees, et al.. (2023). Broad functional profiling of fission yeast proteins using phenomics and machine learning. eLife. 12. 9 indexed citations
5.
Kamrad, Stephan, Clara Correia‐Melo, Łukasz Szyrwiel, et al.. (2023). Metabolic heterogeneity and cross-feeding within isogenic yeast populations captured by DILAC. Nature Microbiology. 8(3). 441–454. 14 indexed citations
6.
Correia‐Melo, Clara, Stephan Kamrad, Roland Tengölics, et al.. (2023). Cell-cell metabolite exchange creates a pro-survival metabolic environment that extends lifespan. Cell. 186(1). 63–79.e21. 32 indexed citations
7.
Rodríguez‐López, Maria, Nicola Bordin, Jonathan Lees, et al.. (2023). Broad functional profiling of fission yeast proteins using phenomics and machine learning. eLife. 12. 9 indexed citations
8.
Gabrielli, Natalia, Eleni Kafkia, Mandy Rettel, et al.. (2023). Unravelling metabolic cross‐feeding in a yeast–bacteria community using 13 C ‐based proteomics. Molecular Systems Biology. 19(4). e11501–e11501. 16 indexed citations
9.
Messner, Christoph B., Vadim Demichev, Julia Muenzner, et al.. (2023). The proteomic landscape of genome-wide genetic perturbations. Cell. 186(9). 2018–2034.e21. 33 indexed citations
10.
Kamrad, Stephan, Jürg Bähler, & Markus Ralser. (2022). High-Throughput, High-Precision Colony Phenotyping with Pyphe. Methods in molecular biology. 2477. 381–397. 5 indexed citations
11.
Kamrad, Stephan, et al.. (2022). Gut reaction: it’s not all about enzymes. Nature Metabolism. 4(10). 1219–1220. 1 indexed citations
12.
Townsend, StJohn, Michał Małecki, Stephan Kamrad, et al.. (2021). Barcode sequencing and a high-throughput assay for chronological lifespan uncover ageing-associated genes in fission yeast. Microbial Cell. 8(7). 146–160. 22 indexed citations
13.
Rodríguez‐López, Maria, Cristina Cotobal, Stephan Kamrad, et al.. (2021). Functional profiling of long intergenic non-coding RNAs in fission yeast. eLife. 11. 8 indexed citations
14.
15.
Kamrad, Stephan, Jan Großbach, Maria Rodríguez‐López, et al.. (2020). Pyruvate kinase variant of fission yeast tunes carbon metabolism, cell regulation, growth and stress resistance. Molecular Systems Biology. 16(4). e9270–e9270. 26 indexed citations
16.
Małecki, Michał, Stephan Kamrad, Markus Ralser, & Jürg Bähler. (2020). Mitochondrial respiration is required to provide amino acids during fermentative proliferation of fission yeast. EMBO Reports. 21(11). e50845–e50845. 32 indexed citations
17.
Kamrad, Stephan, Maria Rodríguez‐López, Cristina Cotobal, et al.. (2020). Pyphe, a python toolbox for assessing microbial growth and cell viability in high-throughput colony screens. eLife. 9. 32 indexed citations
18.
Olín‐Sandoval, Viridiana, Jason Yu, Leonor Miller‐Fleming, et al.. (2019). Lysine harvesting is an antioxidant strategy and triggers underground polyamine metabolism. Nature. 572(7768). 249–253. 120 indexed citations
19.
Zelezniak, Aleksej, Jakob Vowinckel, Floriana Capuano, et al.. (2018). Machine Learning Predicts the Yeast Metabolome from the Quantitative Proteome of Kinase Knockouts. Cell Systems. 7(3). 269–283.e6. 76 indexed citations
20.
Haas, Robert, Aleksej Zelezniak, Jacopo Iacovacci, et al.. (2017). Designing and interpreting ‘multi-omic’ experiments that may change our understanding of biology. Current Opinion in Systems Biology. 6. 37–45. 88 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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