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Related Experiment Video

Updated: Jul 16, 2026

Imaging Molecular Adhesion in Cell Rolling by Adhesion Footprint Assay

Imaging Molecular Adhesion in Cell Rolling by Adhesion Footprint Assay

Published on: September 27, 2021

High-Throughput Focal Adhesion Analysis Software for Automated Detection, Tracking, and Classification of Cell-Matrix

Majid Rostami¹, Sangyoon J Han¹

¹Department of Biomedical Engineering, Michigan Technological University, Houghton, Michigan.

Current Protocols

|July 14, 2026

Summary

This study introduces the Focal Adhesion Package, a MATLAB tool for analyzing cell adhesion dynamics. It automates the detection, tracking, and classification of focal adhesions, revealing their heterogeneous behaviors.

Keywords:

cell migration focal adhesions machine learning nascent adhesions traction force microscopy

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Last Updated: Jul 16, 2026

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Area of Science:

Cell Biology
Biophysics
Image Analysis

Background:

Focal adhesions are crucial multi-protein complexes linking the cytoskeleton to the extracellular matrix.
Migrating cells display over 1000 adhesion structures with diverse, short-lived fates, necessitating advanced analysis methods.

Purpose of the Study:

To present a comprehensive MATLAB-based pipeline for automated analysis of focal adhesion dynamics.
To enable scalable detection, tracking, and machine learning-based classification of individual adhesion trajectories.

Main Methods:

A step-by-step protocol for the Focal Adhesion Package (FAP) pipeline.
Includes image preprocessing, particle detection and tracking, adhesion segmentation, feature extraction, and machine learning classification.
Optional integration with traction force microscopy and multi-channel fluorescence data.

Main Results:

The FAP pipeline automates the analysis of over 1000 focal adhesions in time-lapse fluorescence images.
Achieves machine learning-based classification into 9 functional groups with high efficiency.
Demonstrates efficient processing times, with GPU acceleration significantly reducing runtime.

Conclusions:

The Focal Adhesion Package provides a robust and efficient solution for resolving heterogeneity in focal adhesion dynamics.
Facilitates detailed investigation into protein recruitment, force generation, and adhesion turnover.
Offers a user-friendly graphical interface and script-based automation for broad accessibility.