John E. Dueber

8.8k total citations · 4 hit papers
44 papers, 6.4k citations indexed

About

John E. Dueber is a scholar working on Molecular Biology, Genetics and Organic Chemistry. According to data from OpenAlex, John E. Dueber has authored 44 papers receiving a total of 6.4k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Molecular Biology, 10 papers in Genetics and 6 papers in Organic Chemistry. Recurrent topics in John E. Dueber's work include Microbial Metabolic Engineering and Bioproduction (14 papers), RNA and protein synthesis mechanisms (12 papers) and CRISPR and Genetic Engineering (9 papers). John E. Dueber is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (14 papers), RNA and protein synthesis mechanisms (12 papers) and CRISPR and Genetic Engineering (9 papers). John E. Dueber collaborates with scholars based in United States, Canada and Denmark. John E. Dueber's co-authors include William C. DeLoache, Michael E. Lee, Wendell A. Lim, Kristala L. J. Prather, Gabriel C. Wu, Tae Seok Moon, Jay D. Keasling, Bernardo Cervantes, Zachary N. Russ and G. Reza Malmirchegini and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

John E. Dueber

44 papers receiving 6.3k citations

Hit Papers

Synthetic protein scaffolds provide modular control over ... 2009 2026 2014 2020 2009 2014 2015 2019 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John E. Dueber United States 32 5.6k 965 707 545 538 44 6.4k
Christina D. Smolke United States 49 7.0k 1.2× 957 1.0× 798 1.1× 525 1.0× 1.2k 2.3× 97 7.8k
Kristala L. J. Prather United States 43 6.0k 1.1× 2.2k 2.3× 852 1.2× 734 1.3× 449 0.8× 122 7.1k
Herman van Tilbeurgh France 48 4.5k 0.8× 1.2k 1.2× 594 0.8× 977 1.8× 347 0.6× 148 6.5k
Anton Glieder Austria 48 6.1k 1.1× 1.5k 1.6× 392 0.6× 860 1.6× 389 0.7× 161 7.4k
Blaine A. Pfeifer United States 33 4.9k 0.9× 942 1.0× 592 0.8× 706 1.3× 2.2k 4.1× 115 6.2k
Tom Ellis United Kingdom 37 3.7k 0.7× 910 0.9× 860 1.2× 411 0.8× 163 0.3× 91 4.8k
Keith E. J. Tyo United States 29 4.3k 0.8× 844 0.9× 380 0.5× 522 1.0× 929 1.7× 70 4.9k
Xueqin Lv China 36 2.7k 0.5× 718 0.7× 589 0.8× 496 0.9× 139 0.3× 187 4.0k
Michael C. Jewett United States 61 10.3k 1.8× 1.7k 1.8× 1.6k 2.3× 928 1.7× 532 1.0× 214 11.5k
Amir Aharoni Israel 25 2.6k 0.5× 348 0.4× 354 0.5× 211 0.4× 272 0.5× 75 4.0k

Countries citing papers authored by John E. Dueber

Since Specialization
Citations

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

Fields of papers citing papers by John E. Dueber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John E. Dueber

This figure shows the co-authorship network connecting the top 25 collaborators of John E. Dueber. A scholar is included among the top collaborators of John E. Dueber 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 John E. Dueber. John E. Dueber 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.
Siu, Ka‐Hei, Victoria Lee, & John E. Dueber. (2025). Functional targeting of membrane transporters and enzymes to peroxisomes. Nature Chemical Biology. 21(10). 1544–1553. 2 indexed citations
2.
Guan, Jianguo, et al.. (2025). Nickase fidelity drives EvolvR-mediated diversification in mammalian cells. Nature Communications. 16(1). 3723–3723. 1 indexed citations
3.
Shi, Jie, et al.. (2024). ML-enhanced peroxisome capacity enables compartmentalization of multienzyme pathway. Nature Chemical Biology. 21(5). 727–735. 14 indexed citations
4.
Pyne, Michael E., Kaspar Kevvai, Parbir S. Grewal, et al.. (2020). A yeast platform for high-level synthesis of tetrahydroisoquinoline alkaloids. Nature Communications. 11(1). 3337–3337. 117 indexed citations
5.
Grewal, Parbir S., et al.. (2020). Peroxisome compartmentalization of a toxic enzyme improves alkaloid production. Nature Chemical Biology. 17(1). 96–103. 106 indexed citations
6.
Protzko, Ryan J., Samuel T. Coradetti, Nils Thieme, et al.. (2019). Genomewide and Enzymatic Analysis Reveals Efficient d -Galacturonic Acid Metabolism in the Basidiomycete Yeast Rhodosporidium toruloides. mSystems. 4(6). 23 indexed citations
7.
Langan, Robert A., Scott E. Boyken, Andrew H. Ng, et al.. (2019). De novo design of bioactive protein switches. Nature. 572(7768). 205–210. 185 indexed citations breakdown →
8.
Protzko, Ryan J., et al.. (2019). Iterative screening methodology enables isolation of strains with improved properties for a FACS-based screen and increased L-DOPA production. Scientific Reports. 9(1). 5815–5815. 26 indexed citations
9.
Ng, Andrew H., Taylor H. Nguyen, Mariana Gómez-Schiavon, et al.. (2019). Modular and tunable biological feedback control using a de novo protein switch. Nature. 572(7768). 265–269. 87 indexed citations
10.
Grewal, Parbir S., Cyrus Modavi, Zachary N. Russ, Nicholas C. Harris, & John E. Dueber. (2017). Bioproduction of a betalain color palette in Saccharomyces cerevisiae. Metabolic Engineering. 45. 180–188. 76 indexed citations
11.
Narcross, Lauren, et al.. (2016). Microbial Factories for the Production of Benzylisoquinoline Alkaloids. Trends in biotechnology. 34(3). 228–241. 63 indexed citations
12.
DeLoache, William C., Zachary N. Russ, & John E. Dueber. (2016). Towards repurposing the yeast peroxisome for compartmentalizing heterologous metabolic pathways. Nature Communications. 7(1). 11152–11152. 157 indexed citations
13.
DeLoache, William C., et al.. (2015). An enzyme-coupled biosensor enables (S)-reticuline production in yeast from glucose. Nature Chemical Biology. 11(7). 465–471. 280 indexed citations
15.
Zalatan, Jesse G., Michael E. Lee, Ricardo Almeida, et al.. (2014). Engineering Complex Synthetic Transcriptional Programs with CRISPR RNA Scaffolds. Cell. 160(1-2). 339–350. 734 indexed citations breakdown →
16.
Conrado, Robert, Gabriel C. Wu, Jason T. Boock, et al.. (2011). DNA-guided assembly of biosynthetic pathways promotes improved catalytic efficiency. Nucleic Acids Research. 40(4). 1879–1889. 221 indexed citations
17.
Whitaker, Weston R. & John E. Dueber. (2011). Metabolic Pathway Flux Enhancement by Synthetic Protein Scaffolding. Methods in enzymology on CD-ROM/Methods in enzymology. 497. 447–468. 32 indexed citations
18.
Anderson, J. Christopher, John E. Dueber, Mariana Leguía, et al.. (2010). BglBricks: A flexible standard for biological part assembly. Journal of Biological Engineering. 4(1). 1–1. 335 indexed citations
19.
Moon, Tae Seok, John E. Dueber, Eric Shiue, & Kristala L. J. Prather. (2010). Use of modular, synthetic scaffolds for improved production of glucaric acid in engineered E. coli. Metabolic Engineering. 12(3). 298–305. 236 indexed citations
20.
Dueber, John E., Ethan A. Mirsky, & Wendell A. Lim. (2007). Engineering synthetic signaling proteins with ultrasensitive input/output control. Nature Biotechnology. 25(6). 660–662. 105 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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