Andreas Dräger

7.6k total citations · 1 hit paper
75 papers, 2.4k citations indexed

About

Andreas Dräger is a scholar working on Molecular Biology, Biomedical Engineering and Computational Theory and Mathematics. According to data from OpenAlex, Andreas Dräger has authored 75 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Molecular Biology, 9 papers in Biomedical Engineering and 6 papers in Computational Theory and Mathematics. Recurrent topics in Andreas Dräger's work include Microbial Metabolic Engineering and Bioproduction (53 papers), Bioinformatics and Genomic Networks (40 papers) and Gene Regulatory Network Analysis (31 papers). Andreas Dräger is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (53 papers), Bioinformatics and Genomic Networks (40 papers) and Gene Regulatory Network Analysis (31 papers). Andreas Dräger collaborates with scholars based in Germany, United States and United Kingdom. Andreas Dräger's co-authors include Bernhard Ø. Palsson, Zachary A. King, Ali Ebrahim, Nathan E. Lewis, Andreas Zell, Stephen Federowicz, Philip Miller, Joshua A. Lerman, Nikolaus Sonnenschein and Clemens Wrzodek and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and SHILAP Revista de lepidopterología.

In The Last Decade

Andreas Dräger

70 papers receiving 2.4k citations

Hit Papers

BiGG Models: A platform for integrating, standardizing an... 2015 2026 2018 2022 2015 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andreas Dräger Germany 23 2.1k 492 181 176 108 75 2.4k
Brett G. Olivier Netherlands 22 1.6k 0.8× 418 0.8× 100 0.6× 55 0.3× 39 0.4× 46 1.8k
Isabel Rocha Portugal 32 2.6k 1.2× 1.2k 2.5× 224 1.2× 51 0.3× 84 0.8× 147 3.3k
Katharina Nöh Germany 26 1.9k 0.9× 438 0.9× 117 0.6× 43 0.2× 60 0.6× 83 2.2k
Antje Chang Germany 11 1.3k 0.6× 268 0.5× 90 0.5× 172 1.0× 39 0.4× 13 1.6k
Jan Schellenberger United States 13 2.7k 1.3× 986 2.0× 208 1.1× 106 0.6× 137 1.3× 16 2.9k
Ida Schomburg Germany 12 1.4k 0.6× 269 0.5× 89 0.5× 196 1.1× 40 0.4× 17 1.7k
Laurence Yang United States 26 1.4k 0.6× 436 0.9× 297 1.6× 50 0.3× 40 0.4× 68 1.9k
Hongwu Ma China 30 2.8k 1.3× 671 1.4× 244 1.3× 193 1.1× 88 0.8× 115 3.4k
Maria C. Costanzo United States 28 2.5k 1.2× 110 0.2× 202 1.1× 59 0.3× 38 0.4× 58 3.2k
Anatoly Sorokin Russia 17 1.5k 0.7× 84 0.2× 156 0.9× 194 1.1× 28 0.3× 93 1.9k

Countries citing papers authored by Andreas Dräger

Since Specialization
Citations

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

Fields of papers citing papers by Andreas Dräger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andreas Dräger

This figure shows the co-authorship network connecting the top 25 collaborators of Andreas Dräger. A scholar is included among the top collaborators of Andreas Dräger 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 Andreas Dräger. Andreas Dräger 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.
Renz, Alina, et al.. (2025). Genome-scale metabolic model of Staphylococcus epidermidis ATCC 12228 matches in vitro conditions. mSystems. 10(6). e0041825–e0041825. 1 indexed citations
2.
Renz, Alina, Jonathan Josephs‐Spaulding, Lena Best, et al.. (2025). Metabolic modeling elucidates phenformin and atpenin A5 as broad-spectrum antiviral drugs against RNA viruses. Communications Biology. 8(1). 791–791.
3.
Ostyn, Lisa, et al.. (2024). Genome-scale model of Rothia mucilaginosa predicts gene essentialities and reveals metabolic capabilities. Microbiology Spectrum. 12(6). e0400623–e0400623. 2 indexed citations
4.
Schütz, Monika, et al.. (2024). Exploring the metabolic profile of A. baumannii for antimicrobial development using genome-scale modeling. PLoS Pathogens. 20(9). e1012528–e1012528. 2 indexed citations
5.
Shah, Shalin, et al.. (2021). The systems biology simulation core library. Bioinformatics. 38(3). 864–865. 5 indexed citations
6.
Renz, Alina, et al.. (2021). High-Quality Genome-Scale Reconstruction of Corynebacterium glutamicum ATCC 13032. Frontiers in Microbiology. 12. 750206–750206. 18 indexed citations
7.
Zhang, Fengkai, Lucian P. Smith, Michael L. Blinov, et al.. (2020). Systems biology markup language (SBML) level 3 package: multistate, multicomponent and multicompartment species, version 1, release 2. Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics. 17(2-3). 3 indexed citations
8.
Bergmann, Frank, Tobias Czauderna, Uğur Doğrusöz, et al.. (2020). Systems biology graphical notation markup language (SBGNML) version 0.3. Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics. 17(2-3). 13 indexed citations
9.
Carey, Maureen A., Andreas Dräger, Moritz E. Beber, Jason A. Papin, & James T. Yurkovich. (2020). Community standards to facilitate development and address challenges in metabolic modeling. Molecular Systems Biology. 16(8). e9235–e9235. 34 indexed citations
10.
Gao, Ye, James T. Yurkovich, Sang Woo Seo, et al.. (2018). Systematic discovery of uncharacterized transcription factors in Escherichia coli K-12 MG1655. Nucleic Acids Research. 46(20). 10682–10696. 68 indexed citations
11.
Römer, Michael, et al.. (2016). ZBIT Bioinformatics Toolbox: A Web-Platform for Systems Biology and Expression Data Analysis. PLoS ONE. 11(2). e0149263–e0149263. 15 indexed citations
12.
Du, Bin, Daniel C. Zielinski, Erol Kavvas, et al.. (2016). Evaluation of rate law approximations in bottom-up kinetic models of metabolism. BMC Systems Biology. 10(1). 40–40. 24 indexed citations
13.
Hucka, Michael, Frank Bergmann, Andreas Dräger, et al.. (2015). Systems Biology Markup Language (SBML) Level 2 Version 5: Structures and Facilities for Model Definitions. Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics. 12(2). 731–901. 5 indexed citations
14.
Dräger, Andreas & Bernhard Ø. Palsson. (2014). Improving Collaboration by Standardization Efforts in Systems Biology. Frontiers in Bioengineering and Biotechnology. 2. 61–61. 37 indexed citations
15.
Eichner, Johannes, et al.. (2013). TFpredict and SABINE: Sequence-Based Prediction of Structural and Functional Characteristics of Transcription Factors. PLoS ONE. 8(12). e82238–e82238. 20 indexed citations
16.
Dräger, Andreas. (2011). Computational Modeling of Biochemical Networks. 1–254. 3 indexed citations
17.
Dräger, Andreas, et al.. (2010). Network inference by considering multiple objectives: Insights from in vivo transcriptomic data generated by a synthetic network. 734–742. 1 indexed citations
18.
Dräger, Andreas, et al.. (2009). On the Benefits of Multimodal Optimization for Metablic Network Modeling.. 191–200. 8 indexed citations
19.
Supper, Jochen, et al.. (2009). BowTieBuilder: modeling signal transduction pathways. BMC Systems Biology. 3(1). 67–67. 28 indexed citations
20.
Wrzodek, Clemens, Andreas Dräger, Dierk Wanke, et al.. (2009). ModuleMaster: A new tool to decipher transcriptional regulatory networks. Biosystems. 99(1). 79–81. 9 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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