Daniel J. Cohen

3.7k total citations · 1 hit paper
68 papers, 2.4k citations indexed

About

Daniel J. Cohen is a scholar working on Biomedical Engineering, Molecular Biology and Cell Biology. According to data from OpenAlex, Daniel J. Cohen has authored 68 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Biomedical Engineering, 15 papers in Molecular Biology and 15 papers in Cell Biology. Recurrent topics in Daniel J. Cohen's work include Cellular Mechanics and Interactions (14 papers), 3D Printing in Biomedical Research (13 papers) and Topic Modeling (10 papers). Daniel J. Cohen is often cited by papers focused on Cellular Mechanics and Interactions (14 papers), 3D Printing in Biomedical Research (13 papers) and Topic Modeling (10 papers). Daniel J. Cohen collaborates with scholars based in United States, United Kingdom and France. Daniel J. Cohen's co-authors include Michel M. Maharbiz, Debkishore Mitra, Kevin Peterson, W. James Nelson, David W.L., Talia Y. Moore, Evan Chang-Siu, Thomas Libby, Robert J. Full and Ardian Jusufi and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Daniel J. Cohen

61 papers receiving 2.4k citations

Hit Papers

A Highly Elastic, Capacitive Strain Gauge Based on Percol... 2012 2026 2016 2021 2012 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
Daniel J. Cohen United States 24 897 424 310 237 231 68 2.4k
Min‐Chul Park South Korea 27 423 0.5× 1.2k 2.8× 200 0.6× 204 0.9× 131 0.6× 200 3.1k
Tao Yue China 29 700 0.8× 737 1.7× 87 0.3× 530 2.2× 116 0.5× 164 3.1k
Hiroshi Kikuchi Japan 28 366 0.4× 1.1k 2.7× 250 0.8× 150 0.6× 86 0.4× 180 3.0k
Yoram Palti Israel 32 1.4k 1.6× 1.3k 3.0× 240 0.8× 137 0.6× 37 0.2× 166 4.5k
Elena Pirogova Australia 25 861 1.0× 616 1.5× 86 0.3× 81 0.3× 68 0.3× 127 2.2k
Bing Song United Kingdom 36 1.5k 1.7× 3.2k 7.5× 271 0.9× 324 1.4× 159 0.7× 115 5.6k
Christopher Johnson United States 35 549 0.6× 523 1.2× 193 0.6× 226 1.0× 41 0.2× 171 4.4k
Jean‐Luc Lévêque France 32 739 0.8× 175 0.4× 529 1.7× 48 0.2× 481 2.1× 73 3.8k
Yoko Nakano Japan 34 242 0.3× 1.4k 3.2× 108 0.3× 314 1.3× 107 0.5× 136 4.2k
Shuo Li China 23 403 0.4× 463 1.1× 184 0.6× 68 0.3× 126 0.5× 63 1.9k

Countries citing papers authored by Daniel J. Cohen

Since Specialization
Citations

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

Fields of papers citing papers by Daniel J. Cohen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel J. Cohen. 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 Daniel J. Cohen. The network helps show where Daniel J. Cohen may publish in the future.

Co-authorship network of co-authors of Daniel J. Cohen

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel J. Cohen. A scholar is included among the top collaborators of Daniel J. Cohen 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 Daniel J. Cohen. Daniel J. Cohen 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
2.
Nguyen, Long, et al.. (2025). Large-scale control over collective cell migration using light-activated epidermal growth factor receptors. Cell Systems. 16(3). 101203–101203. 2 indexed citations
3.
Cho, Youn Kyoung, et al.. (2024). E-cadherin biomaterials reprogram collective cell migration and cell cycling by forcing homeostatic conditions. Cell Reports. 43(2). 113743–113743. 11 indexed citations
4.
5.
Cohen, Daniel J.. (2024). Building Biomaterials to Mimic 3D Cell–Cell Junctions. Methods in molecular biology. 2805. 101–112. 1 indexed citations
6.
Zajdel, Tom J., et al.. (2022). Short-term bioelectric stimulation of collective cell migration in tissues reprograms long-term supracellular dynamics. PNAS Nexus. 1(1). pgac002–pgac002. 14 indexed citations
7.
Nirody, Jasmine A., et al.. (2021). Tardigrades exhibit robust interlimb coordination across walking speeds and terrains. Proceedings of the National Academy of Sciences. 118(35). 23 indexed citations
8.
Devenport, Danelle, et al.. (2021). Overriding native cell coordination enhances external programming of collective cell migration. Proceedings of the National Academy of Sciences. 118(29). 30 indexed citations
9.
Zajdel, Tom J., et al.. (2021). Come together: On-chip bioelectric wound closure. Biosensors and Bioelectronics. 192. 113479–113479. 23 indexed citations
10.
Bisaria, Anjali, Arnold Hayer, Damien Garbett, Daniel J. Cohen, & Tobias Meyer. (2020). Membrane-proximal F-actin restricts local membrane protrusions and directs cell migration. Science. 368(6496). 1205–1210. 113 indexed citations
11.
Zajdel, Tom J., et al.. (2020). SCHEEPDOG: Programming Electric Cues to Dynamically Herd Large-Scale Cell Migration. Cell Systems. 10(6). 506–514.e3. 49 indexed citations
12.
Cohen, Daniel J., et al.. (2020). Practical fluorescence reconstruction microscopy for large samples and low-magnification imaging. PLoS Computational Biology. 16(12). e1008443–e1008443. 15 indexed citations
13.
Gloerich, Martijn, et al.. (2017). Cell division orientation is coupled to cell–cell adhesion by the E-cadherin/LGN complex. Nature Communications. 8(1). 13996–13996. 97 indexed citations
14.
Cohen, Daniel J., Martijn Gloerich, & W. James Nelson. (2016). Epithelial self-healing is recapitulated by a 3D biomimetic E-cadherin junction. Proceedings of the National Academy of Sciences. 113(51). 14698–14703. 31 indexed citations
15.
Cohen, Daniel J., et al.. (2015). A review of the effect of omega-3 polyunsaturated fatty acids on blood triacylglycerol levels in normolipidemic and borderline hyperlipidemic individuals. Lipids in Health and Disease. 14(1). 53–53. 107 indexed citations
16.
Libby, Thomas, Talia Y. Moore, Evan Chang-Siu, et al.. (2012). Tail-assisted pitch control in lizards, robots and dinosaurs. Nature. 481(7380). 181–184. 228 indexed citations
17.
Cohen, Daniel J., et al.. (2009). A Modified Consumer Inkjet for Spatiotemporal Control of Gene Expression. PLoS ONE. 4(9). e7086–e7086. 24 indexed citations
18.
Effros, Rita B., Nathalie Boucher, Verna R. Porter, et al.. (1994). Decline in CD28+ T cells in centenarians and in long-term T cell cultures: A possible cause for both in vivo and in vitro immunosenescence. Experimental Gerontology. 29(6). 601–609. 288 indexed citations
19.
Allen, Margaret D., Frank N. Slachman, A. Craig Eddy, et al.. (1991). Tricuspid valve repair for tricuspid valve endocarditis: Tricuspid valve “recycling”. The Annals of Thoracic Surgery. 51(4). 593–598. 25 indexed citations
20.
Milgalter, Eli, Gideon Uretzky, Juri Kopolovic, et al.. (1985). Pericardial meshing: An effective method for prevention of pericardial adhesions and epicardial reaction after cardiac operations. Journal of Thoracic and Cardiovascular Surgery. 90(2). 281–286. 28 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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