Frank J. Bruggeman

7.8k total citations
124 papers, 4.9k citations indexed

About

Frank J. Bruggeman is a scholar working on Molecular Biology, Genetics and Computational Theory and Mathematics. According to data from OpenAlex, Frank J. Bruggeman has authored 124 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 107 papers in Molecular Biology, 29 papers in Genetics and 8 papers in Computational Theory and Mathematics. Recurrent topics in Frank J. Bruggeman's work include Gene Regulatory Network Analysis (74 papers), Microbial Metabolic Engineering and Bioproduction (59 papers) and Bioinformatics and Genomic Networks (33 papers). Frank J. Bruggeman is often cited by papers focused on Gene Regulatory Network Analysis (74 papers), Microbial Metabolic Engineering and Bioproduction (59 papers) and Bioinformatics and Genomic Networks (33 papers). Frank J. Bruggeman collaborates with scholars based in Netherlands, United Kingdom and United States. Frank J. Bruggeman's co-authors include Hans V. Westerhoff, Bas Teusink, Brett G. Olivier, Jorrit J. Hornberg, Fred C. Boogerd, Boris Ν. Kholodenko, Jan Lankelma, Douwe Molenaar, Johan H. van Heerden and Jan B. Hoek and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Frank J. Bruggeman

123 papers receiving 4.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Frank J. Bruggeman Netherlands 38 4.0k 712 538 246 225 124 4.9k
Wolfram Liebermeister Germany 30 4.4k 1.1× 752 1.1× 684 1.3× 175 0.7× 274 1.2× 59 5.3k
Jacky L. Snoep Netherlands 36 4.5k 1.1× 574 0.8× 763 1.4× 176 0.7× 198 0.9× 155 5.7k
Edda Klipp Germany 39 4.4k 1.1× 358 0.5× 495 0.9× 264 1.1× 103 0.5× 161 5.4k
Jörg Stelling Switzerland 31 4.4k 1.1× 624 0.9× 812 1.5× 263 1.1× 72 0.3× 88 5.3k
Dennis Vitkup United States 34 4.3k 1.1× 1.1k 1.5× 613 1.1× 246 1.0× 214 1.0× 44 5.4k
Timothy S. Gardner United States 16 5.8k 1.5× 1.3k 1.8× 698 1.3× 285 1.2× 327 1.5× 28 6.9k
Stefan Schuster Germany 39 3.9k 1.0× 678 1.0× 492 0.9× 120 0.5× 330 1.5× 149 6.0k
Herbert M. Sauro United States 36 3.8k 0.9× 495 0.7× 360 0.7× 183 0.7× 80 0.4× 136 4.3k
Eberhard O. Voit United States 40 4.6k 1.1× 472 0.7× 619 1.2× 294 1.2× 225 1.0× 226 6.5k
Santiago Schnell United States 37 3.0k 0.7× 496 0.7× 381 0.7× 177 0.7× 71 0.3× 158 4.6k

Countries citing papers authored by Frank J. Bruggeman

Since Specialization
Citations

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

Fields of papers citing papers by Frank J. Bruggeman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Frank J. Bruggeman. 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 Frank J. Bruggeman. The network helps show where Frank J. Bruggeman may publish in the future.

Co-authorship network of co-authors of Frank J. Bruggeman

This figure shows the co-authorship network connecting the top 25 collaborators of Frank J. Bruggeman. A scholar is included among the top collaborators of Frank J. Bruggeman 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 Frank J. Bruggeman. Frank J. Bruggeman 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.
Berg, Stefan, et al.. (2024). A temperature-sensitive metabolic valve and a transcriptional feedback loop drive rapid homeoviscous adaptation in Escherichia coli. Nature Communications. 15(1). 9386–9386. 9 indexed citations
2.
Orsi, Enrico, Aleksander J. Kruis, Daniel C. Volke, et al.. (2024). Harnessing noncanonical redox cofactors to advance synthetic assimilation of one-carbon feedstocks. Current Opinion in Biotechnology. 90. 103195–103195. 7 indexed citations
3.
Bruggeman, Frank J., Bas Teusink, & Ralf Steuer. (2023). Trade‐offs between the instantaneous growth rate and long‐term fitness: Consequences for microbial physiology and predictive computational models. BioEssays. 45(10). e2300015–e2300015. 13 indexed citations
4.
Gerber, Alan, et al.. (2023). Understanding spatiotemporal coupling of gene expression using single molecule RNA imaging technologies. Transcription. 14(3-5). 105–126. 2 indexed citations
5.
Gadella, Theodorus W. J., et al.. (2022). Single-cell imaging of ERK and Akt activation dynamics and heterogeneity induced by G-protein-coupled receptors. Journal of Cell Science. 135(6). 12 indexed citations
6.
Bruggeman, Frank J., et al.. (2022). Escherichia coli robustly expresses ATP synthase at growth rate‐maximizing concentrations. FEBS Journal. 289(16). 4925–4934. 8 indexed citations
7.
Elsemman, Ibrahim E., Pranas Grigaitis, Manuel Garcia‐Albornoz, et al.. (2022). Whole-cell modeling in yeast predicts compartment-specific proteome constraints that drive metabolic strategies. Nature Communications. 13(1). 801–801. 57 indexed citations
8.
Gottstein, Willi, et al.. (2021). Selection for Cell Yield Does Not Reduce Overflow Metabolism in Escherichia coli. Molecular Biology and Evolution. 39(1). 9 indexed citations
9.
Botman, Dennis, Tom O’Toole, Joachim Goedhart, et al.. (2021). A yeast FRET biosensor enlightens cAMP signaling. Molecular Biology of the Cell. 32(13). 1229–1240. 15 indexed citations
10.
Nordholt, Niclas, Johan H. van Heerden, & Frank J. Bruggeman. (2020). Biphasic Cell-Size and Growth-Rate Homeostasis by Single Bacillus subtilis Cells. Current Biology. 30(12). 2238–2247.e5. 30 indexed citations
11.
Planqué, Robert, et al.. (2018). Maintaining maximal metabolic flux by gene expression control. PLoS Computational Biology. 14(9). e1006412–e1006412. 11 indexed citations
12.
Bruggeman, Frank J., et al.. (2015). Multiplex Eukaryotic Transcription (In)activation: Timing, Bursting and Cycling of a Ratchet Clock Mechanism. PLoS Computational Biology. 11(4). e1004236–e1004236. 18 indexed citations
13.
Bruggeman, Frank J., et al.. (2015). Fast Flux Module Detection Using Matroid Theory. Journal of Computational Biology. 22(5). 414–424. 2 indexed citations
14.
Blom, Joke, et al.. (2014). Tracing the molecular basis of transcriptional dynamics in noisy data by using an experiment-based mathematical model. Nucleic Acids Research. 43(1). 153–161. 7 indexed citations
15.
16.
Schwabe, Anne, et al.. (2011). Origins of Stochastic Intracellular Processes and Consequences for Cell-to-Cell Variability and Cellular Survival Strategies. Methods in enzymology on CD-ROM/Methods in enzymology. 500. 597–625. 17 indexed citations
17.
Boogerd, Fred C., Frank J. Bruggeman, Jan‐Hendrik S. Hofmeyr, & Hans V. Westerhoff. (2007). Systems Biology: Philosophical Foundations. Data Archiving and Networked Services (DANS). 143 indexed citations
18.
Blüthgen, Nils, Frank J. Bruggeman, Stefan Legewie, et al.. (2006). Effects of sequestration on signal transduction cascades. FEBS Journal. 273(5). 895–906. 126 indexed citations
19.
Boogerd, Fred C., Frank J. Bruggeman, Catholijn M. Jonker, et al.. (2002). Inter-level relations in computer science, biology, and psychology. Philosophical Psychology. 15(4). 463–471. 5 indexed citations
20.
Koebmann, Brian J., Frank J. Bruggeman, Barbara M. Bakker, et al.. (2002). A turbo engine with automatic transmission? How to marry chemicomotion to the subtleties and robustness of life. Biochimica et Biophysica Acta (BBA) - Bioenergetics. 1555(1-3). 75–82. 6 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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