Richard A. Notebaart

3.4k total citations
43 papers, 1.3k citations indexed

About

Richard A. Notebaart is a scholar working on Molecular Biology, Food Science and Biomedical Engineering. According to data from OpenAlex, Richard A. Notebaart has authored 43 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Molecular Biology, 10 papers in Food Science and 7 papers in Biomedical Engineering. Recurrent topics in Richard A. Notebaart's work include Microbial Metabolic Engineering and Bioproduction (28 papers), Bioinformatics and Genomic Networks (12 papers) and Gene Regulatory Network Analysis (8 papers). Richard A. Notebaart is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (28 papers), Bioinformatics and Genomic Networks (12 papers) and Gene Regulatory Network Analysis (8 papers). Richard A. Notebaart collaborates with scholars based in Netherlands, United States and Hungary. Richard A. Notebaart's co-authors include Balázs Papp, Bas Teusink, Eddy J. Smid, Csaba Pál, Roland J. Siezen, Martijn A. Huynen, Christof Francke, Xiaowen Lu, Frank J. M. van Kuppeveld and Daniël Duijsings and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Richard A. Notebaart

42 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Richard A. Notebaart Netherlands 21 1.0k 214 181 162 92 43 1.3k
Minsang Shin South Korea 21 715 0.7× 123 0.6× 349 1.9× 100 0.6× 29 0.3× 75 1.3k
Brady F. Cress United States 22 1.8k 1.8× 191 0.9× 304 1.7× 90 0.6× 38 0.4× 39 2.2k
D. Iserentant Belgium 12 898 0.9× 111 0.5× 277 1.5× 216 1.3× 28 0.3× 31 1.3k
Christina Kurz Germany 13 750 0.7× 51 0.2× 292 1.6× 93 0.6× 126 1.4× 15 1.2k
Osbaldo Reséndis-Antonio Mexico 19 941 0.9× 126 0.6× 172 1.0× 42 0.3× 11 0.1× 49 1.3k
Antonio Jiménez Spain 19 1.1k 1.1× 111 0.5× 271 1.5× 38 0.2× 28 0.3× 39 1.5k
Ying Shi China 18 521 0.5× 38 0.2× 62 0.3× 258 1.6× 31 0.3× 43 1.1k
Hanna Meyer Germany 17 693 0.7× 126 0.6× 173 1.0× 61 0.4× 13 0.1× 23 954
Han Xue China 18 474 0.5× 66 0.3× 127 0.7× 41 0.3× 75 0.8× 70 925

Countries citing papers authored by Richard A. Notebaart

Since Specialization
Citations

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

Fields of papers citing papers by Richard A. Notebaart

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Richard A. Notebaart. 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 Richard A. Notebaart. The network helps show where Richard A. Notebaart may publish in the future.

Co-authorship network of co-authors of Richard A. Notebaart

This figure shows the co-authorship network connecting the top 25 collaborators of Richard A. Notebaart. A scholar is included among the top collaborators of Richard A. Notebaart 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 Richard A. Notebaart. Richard A. Notebaart 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.
Notebaart, Richard A., et al.. (2025). An enzyme activation network reveals extensive regulatory crosstalk between metabolic pathways. Molecular Systems Biology. 21(7). 870–888.
2.
Wijnands, Lucas M., et al.. (2023). Impact of vitamin B12 on rhamnose metabolism, stress defense and in-vitro virulence of Listeria monocytogenes. International Journal of Food Microbiology. 410. 110486–110486. 3 indexed citations
3.
4.
Scott, William T., Oscar van Mastrigt, David E. Block, Richard A. Notebaart, & Eddy J. Smid. (2021). Nitrogenous Compound Utilization and Production of Volatile Organic Compounds among Commercial Wine Yeasts Highlight Strain-Specific Metabolic Diversity. Microbiology Spectrum. 9(1). e0048521–e0048521. 17 indexed citations
5.
6.
Scott, William T., Eddy J. Smid, David E. Block, & Richard A. Notebaart. (2021). Metabolic flux sampling predicts strain-dependent differences related to aroma production among commercial wine yeasts. Microbial Cell Factories. 20(1). 204–204. 15 indexed citations
7.
Boeren, Sjef, et al.. (2021). Bacterial Microcompartment-Dependent 1,2-Propanediol Utilization of Propionibacterium freudenreichii. Frontiers in Microbiology. 12. 679827–679827. 15 indexed citations
8.
Scott, William T., Oscar van Mastrigt, Richard A. Notebaart, Eddy J. Smid, & David E. Block. (2020). Application of a robust dynamic flux balance analysis framework to a wine fermentation for understanding and steering aroma formation. Socio-Environmental Systems Modeling. 1 indexed citations
9.
Guzmán, Gabriela I., Troy E. Sandberg, Ryan A. LaCroix, et al.. (2019). Enzyme promiscuity shapes adaptation to novel growth substrates. Molecular Systems Biology. 15(4). e8462–e8462. 60 indexed citations
10.
Smid, Eddy J., et al.. (2019). Bacterial Microcompartment-Dependent 1,2-Propanediol Utilization Stimulates Anaerobic Growth of Listeria monocytogenes EGDe. Frontiers in Microbiology. 10. 2660–2660. 20 indexed citations
11.
Smid, Eddy J., et al.. (2018). CRISPR-Cas genome engineering of esterase activity in Saccharomyces cerevisiae steers aroma formation. BMC Research Notes. 11(1). 682–682. 22 indexed citations
12.
Notebaart, Richard A., Bálint Kintses, Adam M. Feist, & Balázs Papp. (2017). Underground metabolism: network-level perspective and biotechnological potential. Current Opinion in Biotechnology. 49. 108–114. 43 indexed citations
13.
Megchelenbrink, Wout, Sergio Rossell, Martijn A. Huynen, Richard A. Notebaart, & Elena Marchiori. (2015). Estimating Metabolic Fluxes Using a Maximum Network Flexibility Paradigm. PLoS ONE. 10(10). e0139665–e0139665. 4 indexed citations
14.
Alam, Mohammad Tauqeer, Ganesh R. Manjeri, Richard J. Rodenburg, et al.. (2015). Skeletal muscle mitochondria of NDUFS4−/− mice display normal maximal pyruvate oxidation and ATP production. Biochimica et Biophysica Acta (BBA) - Bioenergetics. 1847(6-7). 526–533. 24 indexed citations
15.
Rossell, Sergio, Martijn A. Huynen, & Richard A. Notebaart. (2013). Inferring Metabolic States in Uncharacterized Environments Using Gene-Expression Measurements. PLoS Computational Biology. 9(3). e1002988–e1002988. 30 indexed citations
16.
Lu, Xiaowen, Philip Kensche, Martijn A. Huynen, & Richard A. Notebaart. (2013). Genome evolution predicts genetic interactions in protein complexes and reveals cancer drug targets. Nature Communications. 4(1). 2124–2124. 27 indexed citations
17.
Papp, Balázs, Balázs Szappanos, & Richard A. Notebaart. (2011). Use of Genome-Scale Metabolic Models in Evolutionary Systems Biology. Methods in molecular biology. 759. 483–497. 9 indexed citations
18.
Papp, Balázs, Richard A. Notebaart, & Csaba Pál. (2011). Systems-biology approaches for predicting genomic evolution. Nature Reviews Genetics. 12(9). 591–602. 97 indexed citations
19.
Papp, Balázs, Bas Teusink, & Richard A. Notebaart. (2008). A critical view of metabolic network adaptations. PubMed. 3(1). 24–35. 46 indexed citations
20.
Wessels, Els, Richard A. Notebaart, Daniël Duijsings, et al.. (2006). Structure-Function Analysis of the Coxsackievirus Protein 3A. Journal of Biological Chemistry. 281(38). 28232–28243. 29 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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