Author

J. Barrasa-Fano

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioengineering· 1 Biophysics· 1 Cell Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Research Focus:cell signaling & trafficking· 2 Approach:statistical model· 2 Approach:deep learning· 1 Research Focus:development & morphogenesis· 1 Approach:experimental assay· 1 Assay:imaging· 1

Frequent Co-Authors

H. Van Oosterwyck· 3 shared J. A. Sanz-Herrera· 2 shared M. Condor· 2 shared A. Apolinar-Fernandez· 1 shared A. Ranga· 1 shared A. Shapeti· 1 shared B. Louis· 1 shared C. Xing· 1 shared

Activity by Year

2020-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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3 shared papersCell Biology

H. Van Oosterwyck

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Author profile →

3 papers

Recent·Most cited

Cell BiologybioRxivNov 16, 2022

Traction force reconstruction assessment on real three-dimensional matrices and cellular morphologies

A. Apolinar-Fernandez, J. Barrasa-Fano, M. Condor…·J. A. Sanz-Herrera

This study assesses the accuracy and efficiency of 3D traction force microscopy (TFM) by evaluating traction reconstruction from synthetic ground truth data under various conditions.

DOI 10.1016/j.ijengsci.2023.103828

statistical modelbenchmarking

𝕏 PostBluesky

BiophysicsbioRxivPreprintAug 24, 2022

Synthetic fibrous hydrogels as a platform to decipher cell-matrix mechanical interactions

H. Yuan, K. Liu, M. Condor…·S. Rocha

This study uses synthetic fibrous hydrogels to investigate cell-matrix mechanical interactions and their impact on cellular behavior.

DOI 10.1101/2022.08.24.505064

experimental assaycell signaling & trafficking

𝕏 PostBluesky

BioengineeringbioRxivDec 8, 2020

Advanced in silico validation framework forthree-dimensional Traction Force Microscopy andapplication to an in vitro model of sproutingangiogenesis

J. Barrasa-Fano, A. Shapeti, J. de Jong…·H. Van Oosterwyck

This paper develops an in silico framework to validate 3D Traction Force Microscopy methods, showing the inverse method outperforms the forward method in accuracy for traction recovery.

DOI 10.1016/j.actbio.2021.03.014

imagingdeep learning

𝕏 PostBluesky