Joep Schmitz

553 total citations
23 papers, 404 citations indexed

About

Joep Schmitz is a scholar working on Molecular Biology, Biomedical Engineering and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Joep Schmitz has authored 23 papers receiving a total of 404 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 8 papers in Biomedical Engineering and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Joep Schmitz's work include Microbial Metabolic Engineering and Bioproduction (11 papers), Mitochondrial Function and Pathology (8 papers) and Advanced MRI Techniques and Applications (5 papers). Joep Schmitz is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (11 papers), Mitochondrial Function and Pathology (8 papers) and Advanced MRI Techniques and Applications (5 papers). Joep Schmitz collaborates with scholars based in Netherlands, United States and Germany. Joep Schmitz's co-authors include Jeroen A. L. Jeneson, Klaas Nicolay, P.A.J. Hilbers, N.A.W. van Riel, Jeanine J. Prompers, Thomas Abeel, María Suárez‐Diez, Carlijn V. C. Bouten, Niels J. B. Driessen and Nicole M. A. van den Broek and has published in prestigious journals such as PLoS ONE, Magnetic Resonance in Medicine and Journal of Biomechanics.

In The Last Decade

Joep Schmitz

23 papers receiving 397 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Joep Schmitz Netherlands 14 194 99 80 77 75 23 404
Paul Roberts United Kingdom 12 94 0.5× 22 0.2× 66 0.8× 68 0.9× 24 0.3× 21 433
Lumme Kadaja Estonia 12 388 2.0× 17 0.2× 77 1.0× 49 0.6× 44 0.6× 18 536
Daniel J. Krause Canada 9 218 1.1× 33 0.3× 44 0.6× 73 0.9× 32 0.4× 16 407
M.L.P. Brückwilder Netherlands 7 242 1.2× 18 0.2× 68 0.8× 25 0.3× 31 0.4× 9 352
Edward P. Bornet United States 9 297 1.5× 41 0.4× 199 2.5× 13 0.2× 47 0.6× 12 501
Zhipeng Feng China 12 92 0.5× 50 0.5× 36 0.5× 12 0.2× 22 0.3× 20 347
G Losano Italy 10 130 0.7× 28 0.3× 160 2.0× 34 0.4× 30 0.4× 43 538
Serkan Gürgül Türkiye 12 100 0.5× 26 0.3× 37 0.5× 8 0.1× 76 1.0× 32 356
Chi‐An W. Emhoff United States 6 77 0.4× 16 0.2× 54 0.7× 125 1.6× 8 0.1× 15 354
Anett Jannasch Germany 11 125 0.6× 18 0.2× 176 2.2× 15 0.2× 38 0.5× 34 383

Countries citing papers authored by Joep Schmitz

Since Specialization
Citations

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

Fields of papers citing papers by Joep Schmitz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joep Schmitz

This figure shows the co-authorship network connecting the top 25 collaborators of Joep Schmitz. A scholar is included among the top collaborators of Joep Schmitz 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 Joep Schmitz. Joep Schmitz 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.
Schmitz, Joep, et al.. (2025). Jaxkineticmodel: Neural ordinary differential equations inspired parameterization of kinetic models. PLoS Computational Biology. 21(7). e1012733–e1012733. 1 indexed citations
2.
Gosiewska, S., et al.. (2024). Machine Learning-Guided Optimization of p -Coumaric Acid Production in Yeast. ACS Synthetic Biology. 13(4). 1312–1322. 15 indexed citations
3.
Santos, Vítor A. P. Martins dos, et al.. (2024). Combinatorial optimization of pathway, process and media for the production of p‐coumaric acid by Saccharomyces cerevisiae. Microbial Biotechnology. 17(3). e14424–e14424. 3 indexed citations
4.
Schmitz, Joep, et al.. (2024). In silico analysis of design of experiment methods for metabolic pathway optimization. Computational and Structural Biotechnology Journal. 23. 1959–1967. 4 indexed citations
5.
Hanko, Erik K. R., Kris Niño G. Valdehuesa, Cunyu Yan, et al.. (2023). Carboxylic acid reductase-dependent biosynthesis of eugenol and related allylphenols. Microbial Cell Factories. 22(1). 238–238. 8 indexed citations
6.
Schmitz, Joep, et al.. (2023). Elucidating yeast glycolytic dynamics at steady state growth and glucose pulses through kinetic metabolic modeling. Metabolic Engineering. 77. 128–142. 12 indexed citations
7.
Schmitz, Joep, et al.. (2023). Simulated Design–Build–Test–Learn Cycles for Consistent Comparison of Machine Learning Methods in Metabolic Engineering. ACS Synthetic Biology. 12(9). 2588–2599. 23 indexed citations
8.
Park, Jong Hyun, Marcelo C. Bassalo, Geng-Min Lin, et al.. (2023). Design of Four Small-Molecule-Inducible Systems in the Yeast Chromosome, Applied to Optimize Terpene Biosynthesis. ACS Synthetic Biology. 12(4). 1119–1132. 15 indexed citations
9.
Schmitz, Joep, et al.. (2022). Enzyme‐constrained models predict the dynamics of Saccharomyces cerevisiae growth in continuous, batch and fed‐batch bioreactors. Microbial Biotechnology. 15(5). 1434–1445. 15 indexed citations
10.
Schmitz, Joep, et al.. (2022). Kinetic Modeling of Saccharomyces cerevisiae Central Carbon Metabolism: Achievements, Limitations, and Opportunities. Metabolites. 12(1). 74–74. 10 indexed citations
11.
Visser, Gepke, Joep Schmitz, Rutger A. J. Nievelstein, et al.. (2016). Altered Energetics of Exercise Explain Risk of Rhabdomyolysis in Very Long-Chain Acyl-CoA Dehydrogenase Deficiency. PLoS ONE. 11(2). e0147818–e0147818. 33 indexed citations
12.
Brussel, Marco van, Joep Schmitz, Klaas Nicolay, et al.. (2015). Muscle Metabolic Responses During Dynamic In-Magnet Exercise Testing. Academic Radiology. 22(11). 1443–1448. 14 indexed citations
13.
14.
Schmitz, Joep, Jeroen A. L. Jeneson, Jeanine J. Prompers, et al.. (2012). Prediction of Muscle Energy States at Low Metabolic Rates Requires Feedback Control of Mitochondrial Respiratory Chain Activity by Inorganic Phosphate. PLoS ONE. 7(3). e34118–e34118. 23 indexed citations
15.
Schmitz, Joep, Joep Vanlier, N.A.W. van Riel, & Jeroen A. L. Jeneson. (2011). Computational Modeling of Mitochondrial Energy Transduction. Critical Reviews in Biomedical Engineering. 39(5). 363–377. 5 indexed citations
16.
Schmitz, Joep, Johannes van Dijk, P.A.J. Hilbers, et al.. (2011). Unchanged muscle fiber conduction velocity relates to mild acidosis during exhaustive bicycling. European Journal of Applied Physiology. 112(5). 1593–1602. 26 indexed citations
17.
Jeneson, Jeroen A. L., Joep Schmitz, Nicole M. A. van den Broek, et al.. (2009). Magnitude and control of mitochondrial sensitivity to ADP. American Journal of Physiology-Endocrinology and Metabolism. 297(3). E774–E784. 39 indexed citations
18.
Schmitz, Joep, N.A.W. van Riel, Klaas Nicolay, P.A.J. Hilbers, & Jeroen A. L. Jeneson. (2009). Silencing of glycolysis in muscle: experimental observation and numerical analysis. Experimental Physiology. 95(2). 380–397. 25 indexed citations
19.
Jeneson, Jeroen A. L., Joep Schmitz, P.A.J. Hilbers, & Klaas Nicolay. (2009). An MR‐compatible bicycle ergometer for in‐magnet whole‐body human exercise testing. Magnetic Resonance in Medicine. 63(1). 257–261. 39 indexed citations
20.
Balguid, Angelique, Niels J. B. Driessen, Anita Mol, et al.. (2008). Stress related collagen ultrastructure in human aortic valves—implications for tissue engineering. Journal of Biomechanics. 41(12). 2612–2617. 44 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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