E. D. Gilles

5.1k total citations
69 papers, 1.4k citations indexed

About

E. D. Gilles is a scholar working on Control and Systems Engineering, Molecular Biology and Materials Chemistry. According to data from OpenAlex, E. D. Gilles has authored 69 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Control and Systems Engineering, 20 papers in Molecular Biology and 8 papers in Materials Chemistry. Recurrent topics in E. D. Gilles's work include Advanced Control Systems Optimization (24 papers), Process Optimization and Integration (17 papers) and Gene Regulatory Network Analysis (12 papers). E. D. Gilles is often cited by papers focused on Advanced Control Systems Optimization (24 papers), Process Optimization and Integration (17 papers) and Gene Regulatory Network Analysis (12 papers). E. D. Gilles collaborates with scholars based in Germany, United States and China. E. D. Gilles's co-authors include Andreas Kremling, Achim Kienle, M. Mangold, Aleksandra Mitrović, Udo Reichl, Katja Bettenbrock, Martin Ginkel, K. D. Mohl, Knut Jahreis and J W Lengeler and has published in prestigious journals such as Bioinformatics, Automatica and Physical Chemistry Chemical Physics.

In The Last Decade

E. D. Gilles

66 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
E. D. Gilles Germany 24 659 419 223 208 118 69 1.4k
E. D. Gilles Germany 18 216 0.3× 399 1.0× 167 0.7× 179 0.9× 111 0.9× 61 1.1k
Shodhan Rao India 17 230 0.3× 284 0.7× 92 0.4× 57 0.3× 76 0.6× 81 945
Philippe Bogaerts Belgium 19 869 1.3× 448 1.1× 156 0.7× 98 0.5× 62 0.5× 110 1.3k
Α. Lübbert Germany 27 1.2k 1.9× 806 1.9× 814 3.7× 79 0.4× 29 0.2× 111 2.3k
Jesús Álvarez Mexico 26 240 0.4× 1.2k 2.8× 159 0.7× 85 0.4× 58 0.5× 186 2.3k
Steven P. Asprey United Kingdom 17 293 0.4× 302 0.7× 126 0.6× 178 0.9× 132 1.1× 27 898
Isao Endo Japan 28 1.2k 1.9× 181 0.4× 714 3.2× 382 1.8× 19 0.2× 123 2.7k
Bernt Nilsson Sweden 25 1.0k 1.6× 130 0.3× 450 2.0× 180 0.9× 54 0.5× 120 1.7k
Andreas Kremling Germany 25 1.4k 2.1× 121 0.3× 266 1.2× 136 0.7× 109 0.9× 77 1.8k
C.B. Lucasius Netherlands 19 222 0.3× 111 0.3× 192 0.9× 180 0.9× 272 2.3× 27 1.3k

Countries citing papers authored by E. D. Gilles

Since Specialization
Citations

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

Fields of papers citing papers by E. D. Gilles

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by E. D. Gilles. 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 E. D. Gilles. The network helps show where E. D. Gilles may publish in the future.

Co-authorship network of co-authors of E. D. Gilles

This figure shows the co-authorship network connecting the top 25 collaborators of E. D. Gilles. A scholar is included among the top collaborators of E. D. Gilles 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 E. D. Gilles. E. D. Gilles 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.
Ederer, Michael, Thomas Sauter, Katja Bettenbrock, Oliver Sawodny, & E. D. Gilles. (2008). Thermodynamically-Consistent Reduced-Order Modeling of the Oxygen Response of Escherichia coli. Max Planck Institute for Plasma Physics.
2.
Gilles, E. D., et al.. (2008). Adapted Pittsburgh Classifier System: Applying Reinforcement Learning Techniques to Meteorological Forecasting. HAL (Le Centre pour la Communication Scientifique Directe). 2 indexed citations
3.
Conradi, Carsten, Julio Sáez-Rodríguez, E. D. Gilles, & Jörg Raisch. (2005). Using chemical reaction network theory to discard a kinetic mechanism hypothesis. PubMed. 152(4). 243–243. 41 indexed citations
4.
Kremling, Andreas, Ralf Heermann, Florian Centler, Kirsten Jung, & E. D. Gilles. (2004). Analysis of two-component signal transduction by mathematical modeling using the KdpD/KdpE system of Escherichia coli. Biosystems. 78(1-3). 23–37. 22 indexed citations
5.
Sáez-Rodríguez, Julio, Andreas Kremling, H. Conzelmann, Katja Bettenbrock, & E. D. Gilles. (2004). Modular analysis of signal transduction networks. IEEE Control Systems. 24(4). 35–52. 51 indexed citations
6.
Bittner, Robert, et al.. (2003). Drift dynamics modeling for automatic track-keeping of inland vessels. Max Planck Institute for Plasma Physics. 218–227. 3 indexed citations
7.
Sauter, Thomas, et al.. (2002). Analysis of the dynamics of the Escherichia coli glucose PTS in different time windows. Max Planck Institute for Plasma Physics. 10(3). 33–42. 1 indexed citations
8.
Gilles, E. D.. (2002). Control-key to better understanding biological systems. Max Planck Institute for Plasma Physics.
9.
Mitrović, Aleksandra, et al.. (2002). Comparison of numerical methods for the simulation of dispersed phase systems. Chemical Engineering Science. 57(20). 4329–4344. 68 indexed citations
10.
Kremling, Andreas, Thomas Sauter, Eric Bullinger, et al.. (2001). Biosystems Engineering: Applying methods from systems theory to biological systems. Open Repository and Bibliography (University of Liège). 282–290. 3 indexed citations
11.
Kremling, Andreas & E. D. Gilles. (2001). The Organization of Metabolic Reaction Networks. Metabolic Engineering. 3(2). 138–150. 51 indexed citations
12.
Kremling, Andreas, Katja Bettenbrock, Britta Laube, et al.. (2001). The Organization of Metabolic Reaction Networks. Metabolic Engineering. 3(4). 362–379. 72 indexed citations
13.
Kremling, Andreas, Knut Jahreis, J W Lengeler, & E. D. Gilles. (2000). The Organization of Metabolic Reaction Networks: A Signal-Oriented Approach to Cellular Models. Metabolic Engineering. 2(3). 190–200. 45 indexed citations
14.
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
15.
Breuel, Gabi, Andreas Kremling, & E. D. Gilles. (1995). An object-oriented approach to the modeling of bacterial metabolism. Systems Analysis Modelling Simulation. 18(9). 813–817. 2 indexed citations
16.
Gerstlauer, Andreas, et al.. (1994). Ein Präprozessor für den verfahrenstechnischen Simulator DIVA. Max Planck Institute for Plasma Physics. 177–182. 2 indexed citations
17.
Marquardt, William H., Andreas Gerstlauer, & E. D. Gilles. (1993). Modeling and representation of complex objects: a chemical engineering perspective. Max Planck Institute for Plasma Physics. 219–228. 7 indexed citations
18.
Reichl, Udo, Rudibert King, & E. D. Gilles. (1992). Effect of temperature and medium composition on mycelial growth of Streptomyces tendae in submerged culture. Journal of Basic Microbiology. 32(3). 193–200. 12 indexed citations
19.
Reichl, Udo, et al.. (1990). An improved method for measuring the interseptal spacing in hyphae of Streptomyces tendae by fluorescence microscopy coupled with image processing. FEMS Microbiology Letters. 67(1-2). 207–210. 22 indexed citations
20.
Reichl, Udo, et al.. (1990). Study of the early growth and branching of Streptomyces tendae by means of an image processing system. Journal of Microscopy. 158(1). 55–62. 34 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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