Automated Author Profile

E.M. De-Juan-Pardo

Current S-Index

4.9

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

1.2

Average Dataset Index per dataset

Total Datasets

4

Total datasets for this author

Average FAIR Score

84.6%

Average FAIR Score per dataset

Total Citations

5

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Validation tool for traction force microscopy

Traction force microscopy (TFM) is commonly used to estimate cells' traction forces from the deformation that they cause on their substrate. The accuracy of TFM highly depends on the computational methods used to measure the deformation of the substrate and estimate the forces, and also on the specifics of the experimental set-up. Computer simulations can be used to evaluate the effect of both the computational methods and the experimental set-up without the need to perform numerous experiments. Here, we present one such TFM simulator that addresses several limitations of the existing ones. As a proof of principle, we recreate a TFM experimental set-up, and apply a classic 2D TFM algorithm to recover the forces. In summary, our simulator provides a valuable tool to study the performance, refine experimentally, and guide the extraction of biological conclusions from TFM experiments.

Authors

  • A. Jorge-Peñas ;
  • A. Muñoz-Barrutia ;
  • E.M. De-Juan-Pardo ;
  • C. Ortiz-De-Solorzano
0 Citations0 Mentions85% FAIR0.3 Dataset Index
10.6084/m9.figshare.11215092015

Validation tool for traction force microscopy

Traction force microscopy (TFM) is commonly used to estimate cells' traction forces from the deformation that they cause on their substrate. The accuracy of TFM highly depends on the computational methods used to measure the deformation of the substrate and estimate the forces, and also on the specifics of the experimental set-up. Computer simulations can be used to evaluate the effect of both the computational methods and the experimental set-up without the need to perform numerous experiments. Here, we present one such TFM simulator that addresses several limitations of the existing ones. As a proof of principle, we recreate a TFM experimental set-up, and apply a classic 2D TFM algorithm to recover the forces. In summary, our simulator provides a valuable tool to study the performance, refine experimentally, and guide the extraction of biological conclusions from TFM experiments.

Authors

  • A. Jorge-Peñas ;
  • A. Muñoz-Barrutia ;
  • E.M. De-Juan-Pardo ;
  • C. Ortiz-De-Solorzano
5 Citations0 Mentions85% FAIR2.4 Dataset Index
10.6084/m9.figshare.1121509.v32015

Validation tool for traction force microscopy

Traction force microscopy (TFM) is commonly used to estimate cells' traction forces from the deformation that they cause on their substrate. The accuracy of TFM highly depends on the computational methods used to measure the deformation of the substrate and estimate the forces, and also on the specifics of the experimental set-up. Computer simulations can be used to evaluate the effect of both the computational methods and the experimental set-up without the need to perform numerous experiments. Here, we present one such TFM simulator that addresses several limitations of the existing ones. As a proof of principle, we recreate a TFM experimental set-up, and apply a classic 2D TFM algorithm to recover the forces. In summary, our simulator provides a valuable tool to study the performance, refine experimentally, and guide the extraction of biological conclusions from TFM experiments.

Authors

  • A. Jorge-Peñas ;
  • A. Muñoz-Barrutia ;
  • E.M. De-Juan-Pardo ;
  • C. Ortiz-De-Solorzano
0 Citations0 Mentions85% FAIR1.8 Dataset Index
10.6084/m9.figshare.1121509.v42015

Validation tool for traction force microscopy

Traction force microscopy (TFM) is commonly used to estimate cells' traction forces from the deformation that they cause on their substrate. The accuracy of TFM highly depends on the computational methods used to measure the deformation of the substrate and estimate the forces, and also on the specifics of the experimental set-up. Computer simulations can be used to evaluate the effect of both the computational methods and the experimental set-up without the need to perform numerous experiments. Here, we present one such TFM simulator that addresses several limitations of the existing ones. As a proof of principle, we recreate a TFM experimental set-up, and apply a classic 2D TFM algorithm to recover the forces. In summary, our simulator provides a valuable tool to study the performance, refine experimentally, and guide the extraction of biological conclusions from TFM experiments.

Authors

  • A. Jorge-Peñas ;
  • A. Muñoz-Barrutia ;
  • E.M. De-Juan-Pardo ;
  • C. Ortiz-De-Solorzano
0 Citations0 Mentions85% FAIR0.3 Dataset Index
10.6084/m9.figshare.1121509.v22014