Nick Papadakis
Impact in
- Molecular Biology top 10%
- Advanced biosensing and bioanalysis techniques
- DNA and Nucleic Acid Chemistry
- RNA Interference and Gene Delivery
- DNA and Biological Computing
- Ecology top 10%
- Bacteriophages and microbial interactions
Papers in
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- Advanced biosensing and bioanalysis techniques 3
- DNA and Nucleic Acid Chemistry 1
- DNA and Biological Computing 1
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- Software Engineering Techniques and Practices 1
- Software Engineering Research 1
- Co-authors
- Erik Winfree (3 shared papers)Paul W. K. Rothemund (3 shared papers)Deborah Kuchnir Fygenson (2 shared papers)Axel Ekani-Nkodo (2 shared papers)Ashish Kumar (1 shared paper)Bruno da Silva (1 shared paper)Joe Sam Robinson (1 shared paper)Kostas N. Fountas (1 shared paper)
- Journals
- Journal of the American Chemical Society (2 papers)Neurosurgery (1 paper)PLoS Biology (1 paper)
- Partner nations
- United States
In The Last Decade
Nick Papadakis
4 papers receiving 883 citations
Nick Papadakis's Hit Papers
Peers
Comparison fields: 5 of 61
- Molecular Biology 807
- Ecology 187
- Biomaterials 64
- Structural Biology 6
- Computational Theory and Mathematics 62
Countries citing papers authored by Nick Papadakis
This map shows the geographic impact of Nick Papadakis'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 Nick Papadakis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nick Papadakis more than expected).
Fields of papers citing papers by Nick Papadakis
This network shows the impact of papers produced by Nick Papadakis. 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 Nick Papadakis. The network helps show where Nick Papadakis may publish in the future.
Co-authors
The 9 scholars most cited alongside Nick Papadakis, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Algorithmic Self-Assembly of DNA Sierpinski Triangles Hit paper breakdown → | 2004 | 513 |
| 2 | 2004 | 393 | |
| 3 | 2020 | 2 | |
| 4 | 2013 | 1 | |
| 5 | 1997 | 0 |
About Nick Papadakis
Nick Papadakis is a scholar working on Molecular Biology, Information Systems, Biomaterials, Radiology, Nuclear Medicine and Imaging and Mechanical Engineering, having authored 5 papers that have together received 909 indexed citations. Recurring topics across this work include Advanced biosensing and bioanalysis techniques (3 papers), Software Engineering Techniques and Practices (1 paper), Molecular Junctions and Nanostructures (1 paper), Advanced MRI Techniques and Applications (1 paper), Software Engineering Research (1 paper), DNA and Nucleic Acid Chemistry (1 paper), Modular Robots and Swarm Intelligence (1 paper) and DNA and Biological Computing (1 paper). The work is most often cited by research in Molecular Biology (807 citations), Ecology (187 citations), Biomaterials (64 citations), Structural Biology (6 citations) and Computational Theory and Mathematics (62 citations). Nick Papadakis has collaborated with scholars based in United States. Frequent co-authors include Erik Winfree, Paul W. K. Rothemund, Deborah Kuchnir Fygenson, Axel Ekani-Nkodo, Ashish Kumar, Bruno da Silva, Joe Sam Robinson, Kostas N. Fountas and Ayan R. Patel. Their work appears in journals such as Journal of the American Chemical Society, Neurosurgery and PLoS Biology.
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.