Martin Ginkel

4.0k total citations
21 papers, 626 citations indexed

About

Martin Ginkel is a scholar working on Molecular Biology, Control and Systems Engineering and Computational Theory and Mathematics. According to data from OpenAlex, Martin Ginkel has authored 21 papers receiving a total of 626 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 5 papers in Control and Systems Engineering and 5 papers in Computational Theory and Mathematics. Recurrent topics in Martin Ginkel's work include Gene Regulatory Network Analysis (7 papers), Microbial Metabolic Engineering and Bioproduction (7 papers) and Bioinformatics and Genomic Networks (5 papers). Martin Ginkel is often cited by papers focused on Gene Regulatory Network Analysis (7 papers), Microbial Metabolic Engineering and Bioproduction (7 papers) and Bioinformatics and Genomic Networks (5 papers). Martin Ginkel collaborates with scholars based in Germany, Switzerland and United States. Martin Ginkel's co-authors include Ernst Dieter Gilles, Steffen Klamt, Jörg Stelling, E. D. Gilles, Su Zhou, Thorsten Schultz, Keith Scott, E. D. Gilles, Kai Sundmacher and Andreas Kremling and has published in prestigious journals such as Bioinformatics, Biophysical Journal and Industrial & Engineering Chemistry Research.

In The Last Decade

Martin Ginkel

20 papers receiving 583 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Martin Ginkel Germany 11 376 155 133 80 75 21 626
Jiahui He China 17 189 0.5× 114 0.7× 37 0.3× 24 0.3× 205 2.7× 52 745
Yanan Liu China 12 79 0.2× 163 1.1× 188 1.4× 36 0.5× 145 1.9× 49 560
Robert Flassig Germany 13 202 0.5× 23 0.1× 74 0.6× 62 0.8× 12 0.2× 24 410
Yanming Wang China 15 129 0.3× 79 0.5× 232 1.7× 5 0.1× 88 1.2× 38 514
Mingyi Zhang China 13 109 0.3× 28 0.2× 65 0.5× 29 0.4× 77 1.0× 52 524
Dequan Li China 8 216 0.6× 63 0.4× 28 0.2× 19 0.2× 27 0.4× 20 422
Hantao Chen China 10 106 0.3× 88 0.6× 19 0.1× 18 0.2× 43 0.6× 33 487
Seunghwan Park South Korea 10 40 0.1× 136 0.9× 17 0.1× 24 0.3× 72 1.0× 50 342
Pratip Rana United States 11 188 0.5× 143 0.9× 9 0.1× 8 0.1× 83 1.1× 32 473

Countries citing papers authored by Martin Ginkel

Since Specialization
Citations

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

Fields of papers citing papers by Martin Ginkel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Ginkel

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Ginkel. A scholar is included among the top collaborators of Martin Ginkel 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 Martin Ginkel. Martin Ginkel 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.
Ginkel, Martin, et al.. (2025). Digital Twins to Support Smart Manufacturing System Design and Ramp up. Procedia CIRP. 134. 933–938.
2.
Li, Tianbo, et al.. (2022). An efficient and scalable data analysis solution for automated electrophysiology platforms. SLAS DISCOVERY. 27(4). 278–285. 1 indexed citations
3.
Li, Tianbo, Martin Ginkel, Renee Emkey, et al.. (2020). Efficient and Highly Scalable Mechanistic Characterization of Ion Channel Function in Drug Discovery. Biophysical Journal. 118(3). 579a–579a. 1 indexed citations
4.
Dahl, Göran, Stephan Steigele, Alexander Mehrle, et al.. (2016). Unified Software Solution for Efficient SPR Data Analysis in Drug Research. SLAS DISCOVERY. 22(2). 203–211. 4 indexed citations
5.
Smith, Lucian P., Michael Hucka, Stefan Hoops, et al.. (2015). SBML Level 3 package: Hierarchical Model Composition, Version 1 Release 3. Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics. 12(2). 603–659. 29 indexed citations
6.
Smith, Lucian P., Michael Hucka, Stefan Hoops, et al.. (2015). SBML Level 3 package: Hierarchical Model Composition, Version 1 Release 3. PubMed. 12(2). 268–268. 25 indexed citations
7.
Smith, Lucian P., Michael Hucka, Stefan Hoops, et al.. (2013). SBML Level 3 Package Specification: Hierarchical Model Composition. CaltechAUTHORS (California Institute of Technology). 3 indexed citations
8.
Ginkel, Martin, et al.. (2009). ProMoT: modular modeling for systems biology. Bioinformatics. 25(5). 687–689. 57 indexed citations
9.
Sáez-Rodríguez, Julio, et al.. (2008). Automatic decomposition of kinetic models of signaling networks minimizing the retroactivity among modules. Bioinformatics. 24(16). i213–i219. 31 indexed citations
10.
Sáez-Rodríguez, Julio, et al.. (2006). Visual setup of logical models of signaling and regulatory networks with ProMoT. BMC Bioinformatics. 7(1). 506–506. 15 indexed citations
11.
Ginkel, Martin, et al.. (2006). Numerical analysis of higher order singularities in chemical process models. Computers & Chemical Engineering. 31(9). 1100–1110. 10 indexed citations
12.
Mangold, M., et al.. (2004). Computer-Aided Modeling of Chemical and Biological Systems:  Methods, Tools, and Applications. Industrial & Engineering Chemistry Research. 44(8). 2579–2591. 9 indexed citations
13.
Kremling, Andreas, et al.. (2004). Workbench zur Modellbildung, Simulation und Analyse zellulärer Systeme (Workbench for Model Set Up, Simulation, and Analysis of Cellular Systems). it - Information Technology. 46(1). 12–19. 1 indexed citations
14.
Ginkel, Martin, et al.. (2003). Application of the Process Modeling Tool ProMoT to large-scale chemical engineering processes. Max Planck Institute for Plasma Physics. 1113–1121. 2 indexed citations
15.
Ginkel, Martin, et al.. (2003). Modular modeling of cellular systems with ProMoT/Diva. Bioinformatics. 19(9). 1169–1176. 70 indexed citations
16.
Klamt, Steffen, Jörg Stelling, Martin Ginkel, & Ernst Dieter Gilles. (2003). FluxAnalyzer: exploring structure, pathways, and flux distributions in metabolic networks on interactive flux maps. Bioinformatics. 19(2). 261–269. 153 indexed citations
17.
Mangold, M., Martin Ginkel, & E. D. Gilles. (2003). A model library for membrane reactors implemented in the process modelling tool ProMoT. Computers & Chemical Engineering. 28(3). 319–332. 17 indexed citations
18.
Sundmacher, Kai, Thorsten Schultz, Su Zhou, et al.. (2001). Dynamics of the direct methanol fuel cell (DMFC): experiments and model-based analysis. Chemical Engineering Science. 56(2). 333–341. 151 indexed citations
19.
Ginkel, Martin, et al.. (2000). PROMOT: A Modeling Tool for Chemical Processes. Mathematical and Computer Modelling of Dynamical Systems. 6(3). 283–307. 38 indexed citations
20.
Ginkel, Martin, et al.. (2000). Application of the process modeling tool PROMOT to the modeling of metabolic networks. Max Planck Institute for Plasma Physics. 525–528. 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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