Erick Moen
Impact in
- Biophysics top 0.2%
- Cell Image Analysis Techniques
- Advanced Fluorescence Microscopy Techniques
- Structural Biology top 5%
Papers in
-
- Microbial Inactivation Methods 11
-
- Cell Image Analysis Techniques 4
- Co-authors
- David Van Valen (3 shared papers)Dylan Bannon (3 shared papers)William D. Graf (3 shared papers)Takamasa Kudo (2 shared papers)Markus W. Covert (1 shared paper)Bennett L. Ibey (11 shared papers)Hope T. Beier (8 shared papers)Caleb C. Roth (6 shared papers)
- Journals
- Nature Methods (2 papers)Bioelectromagnetics (1 paper)Nature Biotechnology (1 paper)Optics Express (1 paper)Biochimica et Biophysica Acta (BBA) - Biomembranes (1 paper)
- Partner nations
- United StatesIsrael
In The Last Decade
Erick Moen
16 papers receiving 1.7k citations
Erick Moen's Hit Papers
Peers
Comparison fields: 5 of 148
- Biophysics 732
- Structural Biology 38
- Media Technology 221
- Biotechnology 123
- Molecular Biology 596
Countries citing papers authored by Erick Moen
This map shows the geographic impact of Erick Moen'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 Erick Moen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Erick Moen more than expected).
Fields of papers citing papers by Erick Moen
This network shows the impact of papers produced by Erick Moen. 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 Erick Moen. The network helps show where Erick Moen may publish in the future.
Co-authors
The 25 scholars most cited alongside Erick Moen, 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 | Deep learning for cellular image analysis Hit paper breakdown → | 2019 | 847 |
| 2 | Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning Hit paper breakdown → | 2021 | 550 |
| 3 | 2021 | 112 | |
| 4 | 2017 | 39 | |
| 5 | 2018 | 24 | |
| 6 | 2014 | 23 | |
| 7 | 2016 | 18 | |
| 8 | 2016 | 15 | |
| 9 | DeepCell 2.0: Automated cloud deployment of deep learning models for large-scale cellular image analysis | 2018 | 9 |
| 10 | 2016 | 9 | |
| 11 | 2016 | 8 | |
| 12 | 2017 | 8 | |
| 13 | 2013 | 6 | |
| 14 | 2015 | 2 | |
| 15 | 2015 | 2 | |
| 16 | 2016 | 1 |
About Erick Moen
Erick Moen is a scholar working on Biotechnology, Biophysics, Biomedical Engineering, Media Technology and Cellular and Molecular Neuroscience, having authored 16 papers that have together received 1.7k indexed citations. Recurring topics across this work include Microbial Inactivation Methods (11 papers), Microfluidic and Bio-sensing Technologies (9 papers), Cell Image Analysis Techniques (4 papers), Single-cell and spatial transcriptomics (3 papers), Neuroscience and Neural Engineering (3 papers), Image Processing Techniques and Applications (3 papers), AI in cancer detection (2 papers) and Photoreceptor and optogenetics research (2 papers). The work is most often cited by research in Biophysics (732 citations), Structural Biology (38 citations), Media Technology (221 citations), Biotechnology (123 citations) and Molecular Biology (596 citations). Erick Moen has collaborated with scholars based in United States and Israel. Frequent co-authors include David Van Valen, Dylan Bannon, William D. Graf, Takamasa Kudo, Markus W. Covert, Bennett L. Ibey, Hope T. Beier, Caleb C. Roth, Brian L. Chang and Noah F. Greenwald. Their work appears in journals such as Nature Methods, Bioelectromagnetics, Nature Biotechnology, Optics Express and Biochimica et Biophysica Acta (BBA) - Biomembranes.
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.