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Neural Processing Letters

, Volume 41, Issue 2, pp 191–200 | Cite as

Bayesian Cell Force Estimation Considering Force Directions

  • Satoshi Kozawa
  • Yuichi Sakumura
  • Michinori Toriyama
  • Naoyuki Inagaki
  • Kazushi Ikeda
Article
  • 189 Downloads

Abstract

Traction force microscopy is a useful technique for measuring mechanical forces generated by cells. In this method, fluorescent nano beads are embedded in the elastic substrate of cell culture, on which cells are cultured. Then, cellular forces are estimated from bead displacements, which represent the force-induced deformation of the substrate under the cell. Estimating the forces from the bead displacements is not easy when the bead density is low or the locations of cellular attachments are unknown. In this study, we propose a Bayesian algorithm by introducing a prior force direction that is based on cellular morphology. We apply the Bayesian framework to synthetic datasets in conditions under which the bead density is low and cellular attachment points are unknown. We demonstrate that the Bayesian algorithm improves accuracy in force estimation compared with the previous algorithms.

Keywords

Traction force microscopy Cellular force estimation  Inverse problem Hierarchical Bayesian model 

Notes

Acknowledgments

This work was supported by a JSPS Grant-in-Aid for Scientific Research (C) (25330341) and Scientific Research on Innovative Areas (25102010).

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Satoshi Kozawa
    • 1
  • Yuichi Sakumura
    • 2
    • 3
  • Michinori Toriyama
    • 3
  • Naoyuki Inagaki
    • 3
  • Kazushi Ikeda
    • 1
  1. 1.Graduate School of Information ScienceNara Institute of Science and TechnologyIkomaJapan
  2. 2.School of Information Science and TechnologyAichi Prefectural UniversityNagakuteJapan
  3. 3.Graduate School of Biological SciencesNara Institute of Science and TechnologyIkomaJapan

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