Sean Seyler
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Fulton Center 300 E University Dr Tempe, AZ 85281
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Mail code: 7805Campus: Tempe
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Sean Seyler is a Senior Project Manager at ASU Health and Adjunct Faculty with the School of Molecular Sciences.
- Postdoctoral Research Scholar – Arizona State University, Department of Physics and Center for Biological Physics
- Ph.D. Physics – Arizona State University, Department of Physics
- M.Eng. Engineering Physics – Cornell University, School of Applied and Engineering Physics
- B.S. Engineering Physics – Cornell University, School of Applied and Engineering Physics
Streaming‑particle method for dielectrophoretic characterization. AKMFK Rasel, EP Ristich, MA Hayes, SL Seyler. Electrophoresis (2025). doi: https://doi.org/10.1002/elps.8146
Gradient insulator‑based dielectrophoresis of gold nanoparticles. A Ramirez, AKMFK Rasel, SL Seyler, MA Hayes. Electrophoresis (2025). doi: https://doi.org/10.1002/elps.8119
Enhanced green fluorescent protein streaming dielectrophoresis in insulator-based microfluidic devices. J Sheu, SL Seyler, AKMFK Rasel, MA Hayes. Electrophoresis (2024). doi: 10.1002/elps.202400123
A numerical study on microfluidic devices to maintain the concentration and purity of dielectrophoresis-induced separated fractions of analyte. AKMFK Rasel, SL Seyler, MA Hayes. Analytical and Bioanalytical Chemistry 415, 4861–4873 (2023). doi: 10.1007/s00216-023-04795-4
Molecular hydrodynamic theory of the velocity autocorrelation function. SL Seyler, CE Seyler. The Journal of Chemical Physics 159(5), 054108 (2023). doi: 10.1063/5.0153649
Surmounting potential barriers: Hydrodynamic memory hedges against thermal fluctuations in particle transport. SL Seyler, S Pressé. The Journal of Chemical Physics 153(4), 041102 (2020). doi: 10.1063/5.0013722
Long-time persistence of hydrodynamic memory boosts microparticle transport. SL Seyler, S Pressé. Physical Review Research 1(3), 032003(R) (2019). doi: 10.1103/PhysRevResearch.1.032003
Hydrodynamic interaction facilitates the unsteady transport of two neighboring vesicles. J Lee, SL Seyler, S Pressé. The Journal of Chemical Physics 151(9), 094108 (2019). doi: 10.1063/1.5113880
Structure of the SLC4 transporter Bor1p in an inward‐facing conformation. N Coudray, SL Seyler, R Lasala, Z Zhang, KM Clark, ME Dumont, A Rohou, O Beckstein, DL Stokes. Protein Science 26(1), 130-145 (2017). doi: 10.1002/pro.3061
MDAnalysis: a Python package for the rapid analysis of molecular dynamics simulations. RJ Gowers, M Linke, J Barnoud, TJE Reddy, MN Melo, SL Seyler, DL Dotson, J Domanski, S Buchoux, IM Kenney, O Beckstein. Proceedings of the 15th Python in Science Conference 98-105 (2016). doi: 10.25080/majora‑629e541a‑00e
datreant: persistent, Pythonic trees for heterogeneous data. DL Dotson, SL Seyler, M Linke, RJ Gowers, O Beckstein. Proceedings of the 15th Python in Science Conference, 51-56 (2016). doi: 10.25080/Majora‑629e541a‑007
Path similarity analysis: a method for quantifying macromolecular pathways. SL Seyler, A Kumar, MF Thorpe, O Beckstein. PLOS Computational Biology 11(10): e1004568 (2015). doi: 10.1371/journal.pcbi.1004568
Sampling large conformational transitions: adenylate kinase as a testing ground. SL Seyler, O Beckstein. Molecular Simulation 40(10-11), 855-877 (2014). doi: 10.1080/08927022.2014.919497