Daniel Merkle

3.0k total citations
75 papers, 1.4k citations indexed

About

Daniel Merkle is a scholar working on Molecular Biology, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Daniel Merkle has authored 75 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Molecular Biology, 16 papers in Artificial Intelligence and 15 papers in Computational Theory and Mathematics. Recurrent topics in Daniel Merkle's work include Microbial Metabolic Engineering and Bioproduction (11 papers), Computational Drug Discovery Methods (9 papers) and Metaheuristic Optimization Algorithms Research (8 papers). Daniel Merkle is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (11 papers), Computational Drug Discovery Methods (9 papers) and Metaheuristic Optimization Algorithms Research (8 papers). Daniel Merkle collaborates with scholars based in Germany, Denmark and Austria. Daniel Merkle's co-authors include Martin Middendorf, Christian Blum, Peter F. Stadler, Matthias Bernt, Christoph Flamm, Jakob L. Andersen, Martin Schlegel, Marleen Perseke, Guido Fritzsch and Kai Ramsch and has published in prestigious journals such as Bioinformatics, European Journal of Operational Research and BMC Bioinformatics.

In The Last Decade

Daniel Merkle

71 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
Daniel Merkle Germany 19 469 316 222 180 165 75 1.4k
Giovanni Felici Italy 20 599 1.3× 205 0.6× 148 0.7× 122 0.7× 70 0.4× 75 1.3k
Michael Kaufmann Germany 25 657 1.4× 180 0.6× 134 0.6× 68 0.4× 336 2.0× 172 2.3k
Gunnar W. Klau Germany 24 1.5k 3.2× 263 0.8× 313 1.4× 66 0.4× 339 2.1× 79 2.5k
Tanya Berger‐Wolf United States 28 276 0.6× 516 1.6× 192 0.9× 439 2.4× 124 0.8× 103 2.6k
Guojun Li China 19 849 1.8× 75 0.2× 152 0.7× 91 0.5× 212 1.3× 93 1.4k
W. H. Day United States 23 653 1.4× 575 1.8× 389 1.8× 137 0.8× 199 1.2× 90 2.4k
Gregory Butler Canada 16 409 0.9× 276 0.9× 84 0.4× 85 0.5× 133 0.8× 68 1.2k
Michael D. Vose United States 24 245 0.5× 1.3k 4.1× 500 2.3× 93 0.5× 520 3.2× 57 2.5k
Marc‐Thorsten Hütt Germany 22 601 1.3× 66 0.2× 173 0.8× 85 0.5× 89 0.5× 108 1.6k
D. F. Robinson New Zealand 14 1.4k 3.0× 220 0.7× 924 4.2× 145 0.8× 91 0.6× 32 2.7k

Countries citing papers authored by Daniel Merkle

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Merkle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Merkle

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Merkle. A scholar is included among the top collaborators of Daniel Merkle 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 Daniel Merkle. Daniel Merkle 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.
Flamm, Christoph, Daniel Merkle, & Peter F. Stadler. (2025). Computation in chemical graph rewriting networks. Journal of Physics Complexity. 6(1). 15014–15014.
2.
3.
Andersen, Jakob L., et al.. (2024). Toward the Reconciliation of Inconsistent Molecular Structures from Biochemical Databases. Journal of Computational Biology. 31(6). 498–512. 2 indexed citations
4.
Andersen, Jakob L., Rolf Fagerberg, Christoph Flamm, et al.. (2022). Representing Catalytic Mechanisms with Rule Composition. Journal of Chemical Information and Modeling. 62(22). 5513–5524. 2 indexed citations
5.
Andersen, Jakob L., et al.. (2019). Combining Graph Transformations and Semigroups for Isotopic Labeling Design. Journal of Computational Biology. 27(2). 269–287. 2 indexed citations
6.
Larsen, Kim S., et al.. (2018). DNA-templated synthesis optimization. Natural Computing. 17(4). 693–707. 2 indexed citations
7.
Andersen, Jakob L., et al.. (2018). Towards mechanistic prediction of mass spectra using graph transformation. University of Southern Denmark Research Portal (University of Southern Denmark). 80(3). 705–731. 2 indexed citations
8.
Andersen, Jakob L., Christoph Flamm, Daniel Merkle, & Peter F. Stadler. (2017). Chemical Transformation Motifs—Modelling Pathways as Integer Hyperflows. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 16(2). 510–523. 30 indexed citations
9.
Andersen, Jakob L., Christoph Flamm, Daniel Merkle, & Peter F. Stadler. (2015). In silico Support for Eschenmoser’s Glyoxylate Scenario. Israel Journal of Chemistry. 55(8). 919–933. 11 indexed citations
10.
Andersen, Jakob L., Christoph Flamm, Martin M. Hanczyc, & Daniel Merkle. (2015). Towards Optimal DNA-Templated Computing. International journal of unconventional computing. 11. 185–203. 1 indexed citations
11.
Andersen, Jakob L., Christoph Flamm, Martin M. Hanczyc, & Daniel Merkle. (2014). Artificial Life 14. MIT Press eBooks. 3 indexed citations
12.
Andersen, Jakob L., Christoph Flamm, Martin M. Hanczyc, & Daniel Merkle. (2014). Towards an Optimal DNA-Templated Molecular Assembler. University of Southern Denmark Research Portal (University of Southern Denmark). 557–564. 1 indexed citations
13.
Merkle, Daniel, Martin Middendorf, & Nicolas Wieseke. (2010). A parameter-adaptive dynamic programming approach for inferring cophylogenies. BMC Bioinformatics. 11(S1). S60–S60. 81 indexed citations
14.
Hellmuth, Marc, Daniel Merkle, & Martin Middendorf. (2009). Extended shapes for the combinatorial design of RNA sequences. International Journal of Computational Biology and Drug Design. 2(4). 371–371. 6 indexed citations
15.
Blum, Christian & Daniel Merkle. (2008). Swarm Intelligence: Introduction and Applications. RMIT Research Repository (RMIT University Library). 43–85. 168 indexed citations
16.
Scheidler, Alexander, Daniel Merkle, & Martin Middendorf. (2008). Stability and performance of ant queue inspired task partitioning methods. Theory in Biosciences. 127(2). 149–161. 5 indexed citations
17.
Perseke, Marleen, Guido Fritzsch, Kai Ramsch, et al.. (2008). Evolution of mitochondrial gene orders in echinoderms. Molecular Phylogenetics and Evolution. 47(2). 855–864. 65 indexed citations
18.
Merkle, Daniel. (2005). Reconstruction of the cophylogenetic history of related phylogenetic trees with divergence timing information. Theory in Biosciences. 123(4). 277–299. 44 indexed citations
19.
Merkle, Daniel & Martin Middendorf. (2002). Studies On The Dynamics Of Ant Colony Optimization Algorithms. Genetic and Evolutionary Computation Conference. 105–112. 8 indexed citations
20.
Louis, Marie-Hélène, David Beck, Daniel Merkle, & Georgianne M. Ciraolo. (1997). Particle size does not affect the rate of intracellular routing for ligands internalized by non-adsorptive pinocytosis. Journal of Electron Microscopy. 46(4). 337–345. 2 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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