Yuan-Jyue Chen

2.2k total citations · 1 hit paper
21 papers, 1.5k citations indexed

About

Yuan-Jyue Chen is a scholar working on Molecular Biology, Electrical and Electronic Engineering and Mechanical Engineering. According to data from OpenAlex, Yuan-Jyue Chen has authored 21 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 4 papers in Electrical and Electronic Engineering and 3 papers in Mechanical Engineering. Recurrent topics in Yuan-Jyue Chen's work include Advanced biosensing and bioanalysis techniques (14 papers), DNA and Biological Computing (9 papers) and DNA and Nucleic Acid Chemistry (7 papers). Yuan-Jyue Chen is often cited by papers focused on Advanced biosensing and bioanalysis techniques (14 papers), DNA and Biological Computing (9 papers) and DNA and Nucleic Acid Chemistry (7 papers). Yuan-Jyue Chen collaborates with scholars based in United States, United Kingdom and Taiwan. Yuan-Jyue Chen's co-authors include Georg Seelig, Benjamin Groves, Richard A. Muscat, Karin Strauß, Andrew Phillips, Luís Ceze, Neil Dalchau, David Soloveichik, Luca Cardelli and Niranjan Srinivas and has published in prestigious journals such as Journal of the American Chemical Society, Nature Communications and Nature Nanotechnology.

In The Last Decade

Yuan-Jyue Chen

21 papers receiving 1.5k citations

Hit Papers

DNA nanotechnology from t... 2015 2026 2018 2022 2015 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yuan-Jyue Chen United States 15 1.4k 319 181 157 114 21 1.5k
Jeff Nivala United States 15 1.1k 0.8× 604 1.9× 165 0.9× 160 1.0× 104 0.9× 26 1.5k
Damien Woods United States 12 737 0.5× 248 0.8× 206 1.1× 180 1.1× 86 0.8× 33 1.0k
David Soloveichik United States 13 2.5k 1.8× 599 1.9× 400 2.2× 170 1.1× 160 1.4× 29 2.7k
Masami Hagiya Japan 14 828 0.6× 169 0.5× 82 0.5× 221 1.4× 48 0.4× 95 1.2k
Reza M. Zadegan United States 15 715 0.5× 208 0.7× 94 0.5× 112 0.7× 70 0.6× 20 823
Chris Dwyer United States 20 779 0.6× 322 1.0× 470 2.6× 76 0.5× 89 0.8× 51 1.2k
Satoshi Kobayashi Japan 14 619 0.5× 175 0.5× 89 0.5× 79 0.5× 38 0.3× 74 1.2k
Elizabeth A. Strychalski United States 17 929 0.7× 549 1.7× 116 0.6× 48 0.3× 66 0.6× 34 1.4k
Nick Papadakis United States 3 807 0.6× 144 0.5× 69 0.4× 136 0.9× 187 1.6× 5 902
Guillaume Gines France 12 810 0.6× 329 1.0× 93 0.5× 52 0.3× 34 0.3× 28 951

Countries citing papers authored by Yuan-Jyue Chen

Since Specialization
Citations

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

Fields of papers citing papers by Yuan-Jyue Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yuan-Jyue Chen. 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 Yuan-Jyue Chen. The network helps show where Yuan-Jyue Chen may publish in the future.

Co-authorship network of co-authors of Yuan-Jyue Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Yuan-Jyue Chen. A scholar is included among the top collaborators of Yuan-Jyue Chen 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 Yuan-Jyue Chen. Yuan-Jyue Chen 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.
Yekhanin, Sergey, Hao Jiang, Jeff Nivala, et al.. (2025). Hybridization-encoded DNA tags with paper-based readout for anti-forgery raw material tracking. Nature Communications. 16(1). 5832–5832. 1 indexed citations
2.
Bögels, Bas W. A., Bichlien H. Nguyen, David P. Schrijver, et al.. (2023). DNA storage in thermoresponsive microcapsules for repeated random multiplexed data access. Nature Nanotechnology. 18(8). 912–921. 39 indexed citations
3.
Nguyen, Bichlien H., Jake A. Smith, Yingce Xia, et al.. (2023). What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarization. PubMed. 2023. 10520–10542. 3 indexed citations
4.
Nguyen, Bichlien H., et al.. (2023). Physical Laboratory Automation in Synthetic Biology. ACS Synthetic Biology. 12(11). 3156–3169. 16 indexed citations
5.
Chen, Yuan-Jyue, et al.. (2022). A nanopore interface for higher bandwidth DNA computing. Nature Communications. 13(1). 4904–4904. 15 indexed citations
6.
Nguyen, Bichlien H., Yuan-Jyue Chen, Jeff Nivala, et al.. (2022). Synthetic DNA applications in information technology. Nature Communications. 13(1). 352–352. 86 indexed citations
7.
Linder, Johannes, et al.. (2021). Robust Digital Molecular Design of Binarized Neural Networks. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 3 indexed citations
8.
Zhang, Jinny Xuemeng, Boyan Yordanov, Alexander L. Gaunt, et al.. (2021). A deep learning model for predicting next-generation sequencing depth from DNA sequence. Nature Communications. 12(1). 4387–4387. 47 indexed citations
9.
Chen, Yuan-Jyue, Xiaomeng Liu, Lee Organick, et al.. (2021). Molecular-level similarity search brings computing to DNA data storage. Nature Communications. 12(1). 4764–4764. 47 indexed citations
10.
Organick, Lee, Yuan-Jyue Chen, Siena Dumas Ang, et al.. (2020). Probing the physical limits of reliable DNA data retrieval. Nature Communications. 11(1). 616–616. 85 indexed citations
11.
Chen, Yuan-Jyue, Christopher N. Takahashi, Lee Organick, et al.. (2020). Quantifying molecular bias in DNA data storage. Nature Communications. 11(1). 3264–3264. 66 indexed citations
12.
Shah, Shalin, Tianqi Song, Luís Ceze, et al.. (2020). Using Strand Displacing Polymerase To Program Chemical Reaction Networks. Journal of the American Chemical Society. 142(21). 9587–9593. 24 indexed citations
13.
Chen, Yuan-Jyue, et al.. (2018). Nucleic Acid Strand Displacement with Synthetic mRNA Inputs in Living Mammalian Cells. ACS Synthetic Biology. 7(12). 2737–2741. 23 indexed citations
14.
Chen, Yuan-Jyue, et al.. (2015). Plasmid-derived DNA Strand Displacement Gates for Implementing Chemical Reaction Networks. Journal of Visualized Experiments. 4 indexed citations
15.
Chen, Yuan-Jyue, et al.. (2015). Plasmid-derived DNA Strand Displacement Gates for Implementing Chemical Reaction Networks. Journal of Visualized Experiments. 2 indexed citations
16.
Groves, Benjamin, Yuan-Jyue Chen, Chiara Zurla, et al.. (2015). Computing in mammalian cells with nucleic acid strand exchange. Nature Nanotechnology. 11(3). 287–294. 187 indexed citations
17.
Chen, Yuan-Jyue, Benjamin Groves, Richard A. Muscat, & Georg Seelig. (2015). DNA nanotechnology from the test tube to the cell. Nature Nanotechnology. 10(9). 748–760. 499 indexed citations breakdown →
18.
Chen, Yuan-Jyue, Neil Dalchau, Niranjan Srinivas, et al.. (2013). Programmable chemical controllers made from DNA. Nature Nanotechnology. 8(10). 755–762. 305 indexed citations
19.
Chen, Yuan-Jyue, et al.. (2009). Multilevel LINC System Designs for Power Efficiency Enhancement of Transmitters. IEEE Journal of Selected Topics in Signal Processing. 3(3). 523–532. 29 indexed citations
20.
Chen, Yuan-Jyue, et al.. (2007). Multilevel Linc System Design for Power Efficiency Enhancement. 53. 31–34. 4 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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