Shailaja Seetharaman

1.3k total citations · 1 hit paper
9 papers, 811 citations indexed

About

Shailaja Seetharaman is a scholar working on Cell Biology, Molecular Biology and Immunology and Allergy. According to data from OpenAlex, Shailaja Seetharaman has authored 9 papers receiving a total of 811 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Cell Biology, 4 papers in Molecular Biology and 2 papers in Immunology and Allergy. Recurrent topics in Shailaja Seetharaman's work include Cellular Mechanics and Interactions (7 papers), Microtubule and mitosis dynamics (4 papers) and Cell Adhesion Molecules Research (2 papers). Shailaja Seetharaman is often cited by papers focused on Cellular Mechanics and Interactions (7 papers), Microtubule and mitosis dynamics (4 papers) and Cell Adhesion Molecules Research (2 papers). Shailaja Seetharaman collaborates with scholars based in France, United States and Singapore. Shailaja Seetharaman's co-authors include Sandrine Etienne‐Manneville, Batiste Boëda, Cécile Leduc, Chiara De Pascalis, Benoît Vianay, Carlos Pérez‐González, Mithila Burute, Nicolas Borghi, Xavier Trepat and Manuel Théry and has published in prestigious journals such as Cell, Nature Materials and The Journal of Cell Biology.

In The Last Decade

Shailaja Seetharaman

9 papers receiving 805 citations

Hit Papers

Cytoskeletal Crosstalk in Cell Migration 2020 2026 2022 2024 2020 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shailaja Seetharaman France 8 493 368 127 95 84 9 811
Lukas D. Osborne United States 6 435 0.9× 465 1.3× 113 0.9× 68 0.7× 79 0.9× 8 772
Ben Stutchbury United Kingdom 5 389 0.8× 311 0.8× 111 0.9× 184 1.9× 86 1.0× 6 684
Annica K. B. Gad Sweden 17 413 0.8× 331 0.9× 87 0.7× 82 0.9× 145 1.7× 31 842
Mark T. Breckenridge United States 8 462 0.9× 295 0.8× 176 1.4× 135 1.4× 55 0.7× 8 739
Lisa Sharek United States 10 471 1.0× 530 1.4× 91 0.7× 79 0.8× 141 1.7× 11 865
Damien Garbett United States 12 435 0.9× 407 1.1× 108 0.9× 81 0.9× 117 1.4× 17 780
Rashmi Priya Australia 15 706 1.4× 588 1.6× 109 0.9× 95 1.0× 86 1.0× 34 1.0k
Xiao Peng United States 7 414 0.8× 316 0.9× 80 0.6× 100 1.1× 55 0.7× 10 673
Asier Jayo United Kingdom 14 327 0.7× 235 0.6× 67 0.5× 135 1.4× 71 0.8× 25 656
Magdalene Michael United Kingdom 13 628 1.3× 399 1.1× 84 0.7× 150 1.6× 67 0.8× 19 864

Countries citing papers authored by Shailaja Seetharaman

Since Specialization
Citations

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

Fields of papers citing papers by Shailaja Seetharaman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shailaja Seetharaman

This figure shows the co-authorship network connecting the top 25 collaborators of Shailaja Seetharaman. A scholar is included among the top collaborators of Shailaja Seetharaman 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 Shailaja Seetharaman. Shailaja Seetharaman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Devany, John, et al.. (2024). Machine learning interpretable models of cell mechanics from protein images. Cell. 187(2). 481–494.e24. 27 indexed citations
2.
Seetharaman, Shailaja, et al.. (2022). Non-catalytic allostery in α-TAT1 by a phospho-switch drives dynamic microtubule acetylation. The Journal of Cell Biology. 221(11). 7 indexed citations
3.
Seetharaman, Shailaja, Benoît Vianay, Aaron J. Farrugia, et al.. (2021). Microtubules tune mechanosensitive cell responses. Nature Materials. 21(3). 366–377. 118 indexed citations
4.
Seetharaman, Shailaja & Sandrine Etienne‐Manneville. (2020). Cytoskeletal Crosstalk in Cell Migration. Trends in Cell Biology. 30(9). 720–735. 282 indexed citations breakdown →
5.
Seetharaman, Shailaja, et al.. (2019). Microtubule acetylation but not detyrosination promotes focal adhesion dynamics and astrocyte migration. Journal of Cell Science. 132(7). 55 indexed citations
6.
Seetharaman, Shailaja & Sandrine Etienne‐Manneville. (2019). Microtubules at focal adhesions – a double-edged sword. Journal of Cell Science. 132(19). 78 indexed citations
7.
Seetharaman, Shailaja & Sandrine Etienne‐Manneville. (2018). Integrin diversity brings specificity in mechanotransduction. Biology of the Cell. 110(3). 49–64. 99 indexed citations
8.
Pascalis, Chiara De, Carlos Pérez‐González, Shailaja Seetharaman, et al.. (2018). Intermediate filaments control collective migration by restricting traction forces and sustaining cell–cell contacts. The Journal of Cell Biology. 217(9). 3031–3044. 107 indexed citations
9.
Seetharaman, Shailaja, Ella Flemyng, Jiazhen Shen, Maria R. Conte, & Anne J. Ridley. (2016). The RNA‐binding protein LARP4 regulates cancer cell migration and invasion. Cytoskeleton. 73(11). 680–690. 38 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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