Paul Matsudaira

22.3k total citations · 6 hit papers
285 papers, 18.2k citations indexed

About

Paul Matsudaira is a scholar working on Molecular Biology, Cell Biology and Biomedical Engineering. According to data from OpenAlex, Paul Matsudaira has authored 285 papers receiving a total of 18.2k indexed citations (citations by other indexed papers that have themselves been cited), including 90 papers in Molecular Biology, 71 papers in Cell Biology and 55 papers in Biomedical Engineering. Recurrent topics in Paul Matsudaira's work include Cellular Mechanics and Interactions (50 papers), Microfluidic and Bio-sensing Technologies (27 papers) and Microfluidic and Capillary Electrophoresis Applications (24 papers). Paul Matsudaira is often cited by papers focused on Cellular Mechanics and Interactions (50 papers), Microfluidic and Bio-sensing Technologies (27 papers) and Microfluidic and Capillary Electrophoresis Applications (24 papers). Paul Matsudaira collaborates with scholars based in United States, Singapore and United Kingdom. Paul Matsudaira's co-authors include David R. Burgess, L. Mahadevan, Jennifer H. Shin, M. L. Gardel, D. A. Weitz, Dana Gabuzda, Jorge Busciglio, Bruce A. Yankner, Utkur Mirsaidov and Roger D. Kamm and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Paul Matsudaira

278 papers receiving 17.7k citations

Hit Papers

Sequence from picomole quantities of proteins electroblot... 1978 2026 1994 2010 1987 2004 2006 1990 1978 1000 2.0k 3.0k 4.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Paul Matsudaira United States 59 7.9k 5.3k 3.1k 1.4k 1.4k 285 18.2k
Denis Wirtz United States 80 8.8k 1.1× 9.5k 1.8× 5.8k 1.8× 943 0.7× 2.3k 1.7× 258 22.5k
Michael W. Davidson United States 65 11.7k 1.5× 5.3k 1.0× 6.3k 2.0× 716 0.5× 2.9k 2.1× 204 26.3k
Ken Jacobson United States 50 8.6k 1.1× 5.1k 1.0× 2.9k 0.9× 1.0k 0.7× 2.4k 1.8× 112 14.2k
Gaudenz Danuser United States 71 8.2k 1.0× 9.9k 1.9× 3.2k 1.0× 852 0.6× 1.4k 1.1× 210 17.7k
Ueli Aebi Switzerland 99 18.2k 2.3× 9.9k 1.9× 1.6k 0.5× 711 0.5× 1.9k 1.4× 318 27.1k
Sherwin J. Singer United States 80 14.3k 1.8× 6.3k 1.2× 2.1k 0.7× 2.3k 1.7× 3.5k 2.6× 246 25.4k
Satyajit Mayor India 60 10.8k 1.4× 5.8k 1.1× 1.4k 0.4× 1.7k 1.2× 961 0.7× 146 15.5k
Donald M. Engelman United States 85 21.0k 2.7× 2.3k 0.4× 1.7k 0.6× 1.4k 1.0× 1.8k 1.3× 250 25.8k
Thomas Walz United States 87 17.5k 2.2× 3.8k 0.7× 1.7k 0.5× 3.5k 2.5× 1.1k 0.8× 271 28.0k
Katharina Gaus Australia 58 6.7k 0.9× 2.1k 0.4× 2.3k 0.7× 1.8k 1.3× 844 0.6× 255 12.2k

Countries citing papers authored by Paul Matsudaira

Since Specialization
Citations

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

Fields of papers citing papers by Paul Matsudaira

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Paul Matsudaira

This figure shows the co-authorship network connecting the top 25 collaborators of Paul Matsudaira. A scholar is included among the top collaborators of Paul Matsudaira 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 Paul Matsudaira. Paul Matsudaira 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.
Marzinek, Jan K., et al.. (2024). Coarse-Grained Model of Glycosaminoglycans for Biomolecular Simulations. Journal of Chemical Theory and Computation. 20(8). 3308–3321. 2 indexed citations
2.
Zhu, Shiwen, et al.. (2024). Receptor binding and tortuosity explain morphogen local-to-global diffusion coefficient transition. Biophysical Journal. 124(6). 963–979. 2 indexed citations
3.
Marzinek, Jan K., Roland G. Huber, Alexander Krah, et al.. (2020). Extending the Martini Coarse-Grained Force Field to N -Glycans. Journal of Chemical Information and Modeling. 60(8). 3864–3883. 29 indexed citations
4.
Nagai, Moeto, Sangjin Ryu, Todd Thorsen, Paul Matsudaira, & Hiroyuki Fujita. (2010). Chemical control of Vorticella bioactuator using microfluidics. Lab on a Chip. 10(12). 1574–1574. 37 indexed citations
5.
Timp, Winston, Utkur Mirsaidov, Paul Matsudaira, & G. Timp. (2008). Jamming prokaryotic cell-to-cell communications in a model biofilm. Lab on a Chip. 9(7). 925–934. 20 indexed citations
6.
Timp, Winston & Paul Matsudaira. (2008). Chapter 14 Electron Microscopy of Hydrated Samples. Methods in cell biology. 89. 391–407. 15 indexed citations
7.
Tarsa, Peter B., Ricardo R. Brau, Mariya Barch, et al.. (2007). Detecting Force‐Induced Molecular Transitions with Fluorescence Resonant Energy Transfer. Angewandte Chemie International Edition. 46(12). 1999–2001. 51 indexed citations
8.
Zaman, Muhammad H., Alisha L. Sieminski, Drew C. MacKellar, et al.. (2006). Migration of tumor cells in 3D matrices is governed by matrix stiffness along with cell-matrix adhesion and proteolysis. Proceedings of the National Academy of Sciences. 103(29). 10889–10894. 926 indexed citations breakdown →
9.
Zaman, Muhammad, Roger D. Kamm, Paul Matsudaira, & Douglas A. Lauffenburger. (2005). Computational Model for Cell Migration in Three-Dimensional Matrices. Biophysical Journal. 89(2). 1389–1397. 193 indexed citations
10.
Evans, James G. & Paul Matsudaira. (2005). Structure and dynamics of macrophage podosomes. European Journal of Cell Biology. 85(3-4). 145–149. 34 indexed citations
11.
Callewaert, Nico, et al.. (2004). Total serum protein N‐glycome profiling on a capillary electrophoresis‐microfluidics platform. Electrophoresis. 25(18-19). 3128–3131. 46 indexed citations
12.
Goedecke, Nils, et al.. (2004). A high‐performance multilane microdevice system designed for the DNA forensics laboratory. Electrophoresis. 25(10-11). 1678–1686. 49 indexed citations
13.
Lodish, Harvey F., Arnold Berk, S Lawrence Zipursky, et al.. (2000). Processing of rRNA and tRNA. 8 indexed citations
14.
Berk, Arnold, et al.. (2000). Protein Glycosylation in the ER and Golgi Complex. 9 indexed citations
15.
Sherman, Michael B., Joanita Jakana, Shujun Sun, et al.. (1999). The three-dimensional structure of the Limulus acrosomal process: a dynamic actin bundle 1 1Edited by W. Baumeister. Journal of Molecular Biology. 294(1). 139–149. 23 indexed citations
16.
Babb, Sherry G., Paul Matsudaira, Masahiko Sato, Ivan Correia, & Soo‐Siang Lim. (1997). Fimbrin in podosomes of monocyte-derived osteoclasts. Cell Motility and the Cytoskeleton. 37(4). 308–325. 67 indexed citations
17.
Adams, A.E., Wenyan Shen, Ching-Shwun Lin, John Leavitt, & Paul Matsudaira. (1995). Isoform-Specific Complementation of the Yeast sac6 Null Mutation by Human Fimbrin. Molecular and Cellular Biology. 15(1). 69–75. 44 indexed citations
18.
Lin, Ching‐Shwun, et al.. (1994). Identification of I-Plastin, a Human Fimbrin Isoform Expressed in Intestine and Kidney. Molecular and Cellular Biology. 14(4). 2457–2467. 37 indexed citations
19.
Matsudaira, Paul. (1990). [45] Limited N-terminal sequence analysis. Methods in enzymology on CD-ROM/Methods in enzymology. 182. 602–613. 164 indexed citations
20.
Matsudaira, Paul, et al.. (1988). Direct protein microsequencing from Immobilon-P Transfer Membrane.. PubMed. 6(2). 154–9. 160 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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