Katharina Nöh

3.8k total citations
83 papers, 2.2k citations indexed

About

Katharina Nöh is a scholar working on Molecular Biology, Biomedical Engineering and Biophysics. According to data from OpenAlex, Katharina Nöh has authored 83 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Molecular Biology, 17 papers in Biomedical Engineering and 12 papers in Biophysics. Recurrent topics in Katharina Nöh's work include Microbial Metabolic Engineering and Bioproduction (50 papers), Metabolomics and Mass Spectrometry Studies (24 papers) and Gene Regulatory Network Analysis (21 papers). Katharina Nöh is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (50 papers), Metabolomics and Mass Spectrometry Studies (24 papers) and Gene Regulatory Network Analysis (21 papers). Katharina Nöh collaborates with scholars based in Germany, United Kingdom and Colombia. Katharina Nöh's co-authors include Wolfgang Wiechert, Sebastian Niedenführ, A. Wahl, Marco Oldiges, Stephan Noack, Dietrich Kohlheyer, Birgit Stute, Stefan Helfrich, Alexander Grünberger and Dany J. V. Beste and has published in prestigious journals such as Nature Communications, Bioinformatics and PLoS ONE.

In The Last Decade

Katharina Nöh

76 papers receiving 2.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Katharina Nöh Germany 26 1.9k 438 208 190 142 83 2.2k
Douglas McCloskey Denmark 22 1.5k 0.8× 304 0.7× 99 0.5× 84 0.4× 60 0.4× 33 1.9k
Mattia Zampieri Switzerland 21 1.2k 0.7× 173 0.4× 110 0.5× 78 0.4× 65 0.5× 36 1.6k
Dong Deng China 16 1.4k 0.7× 138 0.3× 59 0.3× 115 0.6× 96 0.7× 42 2.3k
Andrew Hayes United Kingdom 28 2.0k 1.1× 187 0.4× 261 1.3× 62 0.3× 90 0.6× 56 2.5k
Stephan Noack Germany 30 2.4k 1.3× 1.2k 2.6× 78 0.4× 95 0.5× 75 0.5× 115 3.0k
Fredrik Levander Sweden 31 1.9k 1.0× 188 0.4× 1.1k 5.3× 64 0.3× 96 0.7× 96 3.2k
Michael C. Walsh Netherlands 22 2.2k 1.1× 409 0.9× 204 1.0× 23 0.1× 104 0.7× 28 2.7k
Pierre‐Alain Binz Switzerland 27 2.3k 1.2× 240 0.5× 1.7k 8.1× 89 0.5× 72 0.5× 74 2.9k
Mark Williams United Kingdom 19 1.8k 0.9× 168 0.4× 287 1.4× 30 0.2× 83 0.6× 32 2.4k
Watshara Shoombuatong Thailand 36 2.9k 1.5× 222 0.5× 124 0.6× 84 0.4× 122 0.9× 122 3.7k

Countries citing papers authored by Katharina Nöh

Since Specialization
Citations

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

Fields of papers citing papers by Katharina Nöh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Katharina Nöh

This figure shows the co-authorship network connecting the top 25 collaborators of Katharina Nöh. A scholar is included among the top collaborators of Katharina Nöh 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 Katharina Nöh. Katharina Nöh 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.
Osthege, Michael, et al.. (2024). Automated Processing of Pipelines Managing Now- and Forecasting of Infectious Diseases. elib (German Aerospace Center). 1157–1162. 1 indexed citations
2.
Wiechert, Wolfgang, et al.. (2024). hopsy — a methods marketplace for convex polytope sampling in Python. Bioinformatics. 40(7). 1 indexed citations
3.
Stute, Birgit, T. F. Schulze, Katharina Nöh, et al.. (2024). A microfluidic system for the cultivation of cyanobacteria with precise light intensity and CO 2 control: enabling growth data acquisition at single-cell resolution. Lab on a Chip. 25(3). 319–329. 1 indexed citations
4.
5.
Matamouros, Susana, Thomas Gensch, Johnny Hendriks, et al.. (2023). Growth-rate dependency of ribosome abundance and translation elongation rate in Corynebacterium glutamicum differs from that in Escherichia coli. Nature Communications. 14(1). 5611–5611. 13 indexed citations
6.
Borah, Khushboo, Ye Xu, Catia Costa, et al.. (2023). One‐shot 13 C 15 N ‐metabolic flux analysis for simultaneous quantification of carbon and nitrogen flux. Molecular Systems Biology. 19(3). MSB202211099–MSB202211099. 18 indexed citations
7.
Mitosch, Karin, Prasad Phapale, Bernhard Drotleff, et al.. (2023). A pathogen-specific isotope tracing approach reveals metabolic activities and fluxes of intracellular Salmonella. PLoS Biology. 21(8). e3002198–e3002198. 10 indexed citations
8.
Wiechert, Wolfgang, et al.. (2022). CellSium: versatile cell simulator for microcolony ground truth generation. Bioinformatics Advances. 2(1). vbac053–vbac053. 1 indexed citations
9.
Scherr, Tim, et al.. (2022). microbeSEG: A deep learning software tool with OMERO data management for efficient and accurate cell segmentation. PLoS ONE. 17(11). e0277601–e0277601. 8 indexed citations
10.
Strohmeier, Daniel, Katharina Nöh, Dietrich Kohlheyer, et al.. (2022). Communities of Niche-optimized Strains (CoNoS) – Design and creation of stable, genome-reduced co-cultures. Metabolic Engineering. 73. 91–103. 10 indexed citations
11.
Nöh, Katharina, et al.. (2021). PolyRound: polytope rounding for random sampling in metabolic networks. Bioinformatics. 38(2). 566–567. 7 indexed citations
12.
Wiechert, Wolfgang, et al.. (2019). The Design of FluxML: A Universal Modeling Language for 13C Metabolic Flux Analysis. Frontiers in Microbiology. 10. 1022–1022. 22 indexed citations
13.
Mackfeld, Ursula, Friederike Hoffmann, Katharina Nöh, et al.. (2018). Towards a Mechanistic Understanding of Factors Controlling the Stereoselectivity of Transketolase. ChemCatChem. 10(12). 2601–2611. 1 indexed citations
14.
Nöh, Katharina, et al.. (2018). A Pareto approach to resolve the conflict between information gain and experimental costs: Multiple-criteria design of carbon labeling experiments. PLoS Computational Biology. 14(10). e1006533–e1006533. 20 indexed citations
15.
Delp, Johannes, Simon Gutbier, Christin Zasada, et al.. (2017). Stage-specific metabolic features of differentiating neurons: Implications for toxicant sensitivity. Toxicology and Applied Pharmacology. 354. 64–80. 23 indexed citations
16.
Krämer, Christina, Abhijeet Singh, Stefan Helfrich, et al.. (2015). Non-Invasive Microbial Metabolic Activity Sensing at Single Cell Level by Perfusion of Calcein Acetoxymethyl Ester. PLoS ONE. 10(10). e0141768–e0141768. 16 indexed citations
17.
Bartek, Tobias, Bastian Blombach, Siegmund Lang, et al.. (2011). Comparative13C Metabolic Flux Analysis of Pyruvate Dehydrogenase Complex-Deficient,l-Valine-Producing Corynebacterium glutamicum. Applied and Environmental Microbiology. 77(18). 6644–6652. 54 indexed citations
18.
Noack, Stephan, et al.. (2010). Stationary versus non-stationary 13C-MFA: A comparison using a consistent dataset. Journal of Biotechnology. 154(2-3). 179–190. 51 indexed citations
19.
Noack, Stephan, et al.. (2009). Customizable Visualization of Multi-omics Data in the Context of Biochemical Networks. 295. 21–25. 5 indexed citations
20.
Wiechert, Wolfgang, et al.. (2007). The topology of metabolic isotope labeling networks. BMC Bioinformatics. 8(1). 315–315. 28 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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