Daiki Umetsu

1.5k total citations
27 papers, 1.1k citations indexed

About

Daiki Umetsu is a scholar working on Molecular Biology, Cell Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Daiki Umetsu has authored 27 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 13 papers in Cell Biology and 12 papers in Cellular and Molecular Neuroscience. Recurrent topics in Daiki Umetsu's work include Neurobiology and Insect Physiology Research (11 papers), Developmental Biology and Gene Regulation (11 papers) and Cellular Mechanics and Interactions (10 papers). Daiki Umetsu is often cited by papers focused on Neurobiology and Insect Physiology Research (11 papers), Developmental Biology and Gene Regulation (11 papers) and Cellular Mechanics and Interactions (10 papers). Daiki Umetsu collaborates with scholars based in Japan, Germany and France. Daiki Umetsu's co-authors include Tetsuya Tabata, Tetsuo Yasugi, Christian Dahmann, Makoto Sato, Satoshi Murakami, Benoît Aigouy, Frank Jülicher, Suzanne Eaton, Atsushi Sugie and Reza Farhadifar and has published in prestigious journals such as Nature Communications, Genes & Development and Nature Neuroscience.

In The Last Decade

Daiki Umetsu

26 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daiki Umetsu Japan 15 717 567 413 132 106 27 1.1k
Claire Bertet France 8 807 1.1× 723 1.3× 485 1.2× 139 1.1× 157 1.5× 9 1.3k
Kaoru Sugimura Japan 17 591 0.8× 982 1.7× 418 1.0× 93 0.7× 284 2.7× 31 1.5k
Matthieu Cavey France 10 422 0.6× 410 0.7× 287 0.7× 108 0.8× 75 0.7× 11 982
Cédric Maurange France 17 850 1.2× 169 0.3× 403 1.0× 182 1.4× 80 0.8× 21 1.1k
Patricia Kunda Argentina 14 842 1.2× 1.2k 2.1× 311 0.8× 63 0.5× 118 1.1× 20 1.7k
Catarina C. F. Homem Portugal 13 884 1.2× 461 0.8× 344 0.8× 122 0.9× 24 0.2× 22 1.3k
Asako Tsubouchi Japan 15 543 0.8× 328 0.6× 486 1.2× 65 0.5× 28 0.3× 17 1.1k
Juliette Mathieu France 15 788 1.1× 611 1.1× 140 0.3× 64 0.5× 72 0.7× 24 1.2k
Katherine W. Rogers United States 13 1.1k 1.5× 430 0.8× 138 0.3× 104 0.8× 151 1.4× 22 1.4k

Countries citing papers authored by Daiki Umetsu

Since Specialization
Citations

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

Fields of papers citing papers by Daiki Umetsu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daiki Umetsu. 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 Daiki Umetsu. The network helps show where Daiki Umetsu may publish in the future.

Co-authorship network of co-authors of Daiki Umetsu

This figure shows the co-authorship network connecting the top 25 collaborators of Daiki Umetsu. A scholar is included among the top collaborators of Daiki Umetsu 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 Daiki Umetsu. Daiki Umetsu 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.
Nagai, Hiroki, Luís Augusto Eijy Nagai, Ryuichiro Nakato, et al.. (2023). Nutrient-driven dedifferentiation of enteroendocrine cells promotes adaptive intestinal growth in Drosophila. Developmental Cell. 58(18). 1764–1781.e10. 6 indexed citations
2.
Fujita, Hideaki, Junichi Kaneshiro, Maki Takeda, et al.. (2023). Estimation of crossbridge-state during cardiomyocyte beating using second harmonic generation. Life Science Alliance. 6(7). e202302070–e202302070. 5 indexed citations
3.
Umetsu, Daiki. (2022). Sample Preparation and Imaging of the Pupal Drosophila Abdominal Epidermis. Methods in molecular biology. 2540. 335–347.
4.
Sato, Katsuhiko & Daiki Umetsu. (2021). A Novel Cell Vertex Model Formulation that Distinguishes the Strength of Contraction Forces and Adhesion at Cell Boundaries. Frontiers in Physics. 9. 5 indexed citations
5.
Sato, Katsuhiko, et al.. (2020). Differential cell adhesion implemented by Drosophila Toll corrects local distortions of the anterior-posterior compartment boundary. Nature Communications. 11(1). 6320–6320. 15 indexed citations
6.
Ohsawa, Shizue, et al.. (2018). Competition for Space Is Controlled by Apoptosis-Induced Change of Local Epithelial Topology. Current Biology. 28(13). 2115–2128.e5. 42 indexed citations
7.
Umetsu, Daiki & Erina Kuranaga. (2017). Planar polarized contractile actomyosin networks in dynamic tissue morphogenesis. Current Opinion in Genetics & Development. 45. 90–96. 7 indexed citations
8.
Umetsu, Daiki, et al.. (2017). Inference of Cell Mechanics in Heterogeneous Epithelial Tissue Based on Multivariate Clone Shape Quantification. Frontiers in Cell and Developmental Biology. 5. 68–68. 7 indexed citations
9.
Aigouy, Benoît, Daiki Umetsu, & Suzanne Eaton. (2016). Segmentation and Quantitative Analysis of Epithelial Tissues. Methods in molecular biology. 1478. 227–239. 96 indexed citations
10.
11.
Umetsu, Daiki, et al.. (2014). Local Increases in Mechanical Tension Shape Compartment Boundaries by Biasing Cell Intercalations. Current Biology. 24(15). 1798–1805. 71 indexed citations
12.
Umetsu, Daiki, Sebastian Dunst, & Christian Dahmann. (2014). An RNA Interference Screen for Genes Required to Shape the Anteroposterior Compartment Boundary in Drosophila Identifies the Eph Receptor. PLoS ONE. 9(12). e114340–e114340. 19 indexed citations
13.
Yasugi, Tetsuo, Atsushi Sugie, Daiki Umetsu, & Tetsuya Tabata. (2010). Coordinated sequential action of EGFR and Notch signaling pathways regulates proneural wave progression in the Drosophila optic lobe. Development. 137(19). 3193–3203. 86 indexed citations
14.
Umetsu, Daiki & Christian Dahmann. (2010). Compartment boundaries. Fly. 4(3). 241–245. 14 indexed citations
15.
Sugie, Atsushi, Daiki Umetsu, Tetsuo Yasugi, Karl‐Friedrich Fischbach, & Tetsuya Tabata. (2010). Recognition of pre- and postsynaptic neurons via nephrin/NEPH1 homologs is a basis for the formation of theDrosophilaretinotopic map. Development. 137(19). 3303–3313. 39 indexed citations
16.
Sawatsubashi, Shun, Takuya Murata, Ryoji Fujiki, et al.. (2009). A histone chaperone, DEK, transcriptionally coactivates a nuclear receptor. Genes & Development. 24(2). 159–170. 120 indexed citations
17.
Farhadifar, Reza, Jonas Ranft, Daiki Umetsu, et al.. (2009). Increased Cell Bond Tension Governs Cell Sorting at the Drosophila Anteroposterior Compartment Boundary. Current Biology. 19(22). 1950–1955. 245 indexed citations
18.
Murakami, Satoshi, et al.. (2007). Focal adhesion kinase controls morphogenesis of theDrosophilaoptic stalk. Development. 134(8). 1539–1548. 23 indexed citations
19.
Umetsu, Daiki, Satoshi Murakami, Makoto Sato, & Tetsuya Tabata. (2006). The highly ordered assembly of retinal axons and their synaptic partners is regulated by Hedgehog/Single-minded in theDrosophilavisual system. Development. 133(5). 791–800. 37 indexed citations
20.
Sato, Makoto, Daiki Umetsu, Satoshi Murakami, Tetsuo Yasugi, & Tetsuya Tabata. (2005). DWnt4 regulates the dorsoventral specificity of retinal projections in the Drosophila melanogaster visual system. Nature Neuroscience. 9(1). 67–75. 66 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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