David J. Odde

10.7k total citations · 2 hit papers
127 papers, 6.6k citations indexed

About

David J. Odde is a scholar working on Cell Biology, Molecular Biology and Biomedical Engineering. According to data from OpenAlex, David J. Odde has authored 127 papers receiving a total of 6.6k indexed citations (citations by other indexed papers that have themselves been cited), including 95 papers in Cell Biology, 57 papers in Molecular Biology and 29 papers in Biomedical Engineering. Recurrent topics in David J. Odde's work include Microtubule and mitosis dynamics (63 papers), Cellular Mechanics and Interactions (57 papers) and Photosynthetic Processes and Mechanisms (19 papers). David J. Odde is often cited by papers focused on Microtubule and mitosis dynamics (63 papers), Cellular Mechanics and Interactions (57 papers) and Photosynthetic Processes and Mechanisms (19 papers). David J. Odde collaborates with scholars based in United States, Germany and France. David J. Odde's co-authors include Melissa K. Gardner, Michael J. Renn, Lynne Cassimeris, Yaakov Nahmias, Vincent VanBuren, Benjamin L. Bangasser, Kerry Bloom, Steven S. Rosenfeld, Brian T. Castle and Helen M. Buettner and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

David J. Odde

125 papers receiving 6.5k citations

Hit Papers

Traction Dynamics of Filopodia on Compliant Substrates 2008 2026 2014 2020 2008 2022 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David J. Odde United States 44 4.3k 3.0k 1.9k 569 561 127 6.6k
Iva M. Tolić Croatia 36 3.8k 0.9× 2.3k 0.8× 1.4k 0.8× 488 0.9× 789 1.4× 105 5.5k
Manuel Théry France 49 6.4k 1.5× 3.9k 1.3× 2.6k 1.4× 336 0.6× 653 1.2× 103 9.3k
Buzz Baum United Kingdom 53 5.2k 1.2× 4.6k 1.5× 1.1k 0.6× 372 0.7× 284 0.5× 132 8.6k
Ewa K. Paluch United Kingdom 37 5.2k 1.2× 2.5k 0.8× 1.9k 1.0× 159 0.3× 751 1.3× 57 7.1k
Timothy J. Mitchison United States 35 5.6k 1.3× 4.0k 1.4× 1.2k 0.6× 334 0.6× 573 1.0× 39 8.5k
Matthieu Piel France 60 6.8k 1.6× 5.0k 1.7× 3.1k 1.6× 429 0.8× 478 0.9× 153 11.5k
Aurélien Roux Switzerland 47 4.8k 1.1× 6.7k 2.3× 961 0.5× 246 0.4× 862 1.5× 120 9.8k
G. V. Shivashankar Singapore 40 2.4k 0.5× 3.2k 1.1× 1.0k 0.5× 425 0.7× 346 0.6× 151 5.7k
Sean X. Sun United States 43 2.7k 0.6× 2.3k 0.8× 1.6k 0.8× 145 0.3× 644 1.1× 132 5.3k
Pierre‐François Lenne France 36 3.6k 0.8× 3.2k 1.1× 1.9k 1.0× 140 0.2× 1000 1.8× 88 6.7k

Countries citing papers authored by David J. Odde

Since Specialization
Citations

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

Fields of papers citing papers by David J. Odde

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David J. Odde

This figure shows the co-authorship network connecting the top 25 collaborators of David J. Odde. A scholar is included among the top collaborators of David J. Odde 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 David J. Odde. David J. Odde 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.
Odde, David J., et al.. (2025). Allocation of resources among multiple daughter cells. The Journal of Cell Biology. 224(11).
2.
Provenzano, Paolo P., et al.. (2025). Physical principles and mechanisms of cell migration. PubMed. 2(1). 2–2. 8 indexed citations
3.
Hou, Jay, et al.. (2024). Cell migration simulator-based biomarkers for glioblastoma. Neuro-Oncology Advances. 6(1). vdae184–vdae184. 1 indexed citations
4.
Shamsan, Ghaidan A., et al.. (2024). Mutual antagonism between CD44 and integrins in glioblastoma cell traction and migration. APL Bioengineering. 8(3). 36102–36102. 4 indexed citations
5.
Ramírez, María Paz, Ghaidan A. Shamsan, Sarah M. Anderson, et al.. (2023). RAD-TGTs: high-throughput measurement of cellular mechanotype via rupture and delivery of DNA tension probes. Nature Communications. 14(1). 2468–2468. 10 indexed citations
6.
Schaller, Matthew, Juan Manuel Urueña, Julia C. Loeb, et al.. (2021). Ex vivo SARS-CoV-2 infection of human lung reveals heterogeneous host defense and therapeutic responses. JCI Insight. 6(18). 29 indexed citations
7.
Kenchappa, Rajappa S., Vandana Rai, James F. Crish, et al.. (2019). Myosin IIA suppresses glioblastoma development in a mechanically sensitive manner. Proceedings of the National Academy of Sciences. 116(31). 15550–15559. 43 indexed citations
8.
Rosenfeld, Steven S., et al.. (2018). A Brownian dynamics tumor progression simulator with application to glioblastoma. PubMed. 4(1). 15001–15001. 13 indexed citations
9.
Shamsan, Ghaidan A., Susan K. Rathe, Ingrid Cornax, et al.. (2016). Slit-Robo GTPase-Activating Protein 2 as a metastasis suppressor in osteosarcoma. Scientific Reports. 6(1). 39059–39059. 28 indexed citations
10.
Čekan, Pavol, Keisuke Hasegawa, Yu Pan, et al.. (2016). RCC1-dependent activation of Ran accelerates cell cycle and DNA repair, inhibiting DNA damage–induced cell senescence. Molecular Biology of the Cell. 27(8). 1346–1357. 39 indexed citations
11.
Hepperla, Austin J., Courtney Coombes, Maryam Gerami‐Nejad, et al.. (2014). Minus-End-Directed Kinesin-14 Motors Align Antiparallel Microtubules to Control Metaphase Spindle Length. Developmental Cell. 31(1). 61–72. 63 indexed citations
12.
Gardner, Melissa K., et al.. (2011). Microtubule Tip Tracking and Tip Structures at the Nanometer Scale Using Digital Fluorescence Microscopy. Cellular and Molecular Bioengineering. 4(2). 192–204. 44 indexed citations
13.
Gardner, Melissa K., Chad G. Pearson, Brian L. Sprague, et al.. (2005). Tension-dependent Regulation of Microtubule Dynamics at Kinetochores Can Explain Metaphase Congression in Yeast. Molecular Biology of the Cell. 16(8). 3764–3775. 103 indexed citations
14.
Odde, David J.. (2005). Mitotic Spindle: Disturbing a Subtle Balance. Current Biology. 15(23). R956–R959. 5 indexed citations
15.
Paulsen, J. A., et al.. (2005). Two‐step cell patterning on planar and complex curved surfaces by precision spraying of polymers. Biotechnology and Bioengineering. 93(5). 919–927. 41 indexed citations
16.
Fass, Joseph & David J. Odde. (2003). Tensile Force-Dependent Neurite Elicitation via Anti-β1 Integrin Antibody-Coated Magnetic Beads. Biophysical Journal. 85(1). 623–636. 92 indexed citations
17.
Sprague, Brian L., Chad G. Pearson, Paul S. Maddox, et al.. (2003). Mechanisms of Microtubule-Based Kinetochore Positioning in the Yeast Metaphase Spindle. Biophysical Journal. 84(6). 3529–3546. 82 indexed citations
18.
Odde, David J. & Michael J. Renn. (1999). Laser-guided direct writing for applications in biotechnology. Trends in biotechnology. 17(10). 385–389. 196 indexed citations
19.
Odde, David J., et al.. (1997). COMPUTER-ASSISTED MOTION ANALYSIS OF FLUORESCENT TUBULIN DYNAMICS IN THE NERVE GROWTH CONE. 9(3). 143–151. 1 indexed citations
20.
Yarmush, Martin L., et al.. (1992). Immunoaffinity purification: Basic principles and operational considerations. Biotechnology Advances. 10(3). 413–446. 29 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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