BARCODE: Biomaterial Activity Readouts to Categorize, Optimize, Design and Engineer for high throughput screening and characterization of dynamically restructuring soft materials

TL;DR

BARCODE is an open-source software that automates high throughput microscopy video analysis to efficiently characterize and optimize dynamic, nonequilibrium soft materials, significantly reducing data complexity and enabling broad accessibility.

Contribution

It introduces a novel, multiparametric fingerprinting approach for analyzing complex material datasets, facilitating rapid screening and discovery of responsive soft materials.

Findings

Successfully analyzed cytoskeleton networks and cell monolayers datasets.

Reduced data dimensionality and size while retaining rich information.

Enabled non-expert access and comparison of complex material data.

Abstract

Active, responsive, nonequilibrium materials, at the forefront of materials engineering, offer dynamical restructuring, mobility and other complex life-like properties. Yet, this enhanced functionality comes with significant amplification of the size and complexity of the datasets needed to characterize their properties, thereby challenging conventional approaches to analysis. To meet this need, we present BARCODE (Biomaterial Activity Readouts to Categorize, Optimize, Design and Engineer), an open-access software that automates high throughput screening of microscopy video data to enable nonequilibrium material optimization and discovery. BARCODE produces a unique fingerprint or barcode of performance metrics that visually and quantitatively encodes dynamic material properties with minimal file size. Using three complementary material agnostic analysis branches, BARCODE significantly reduces data dimensionality and size, while providing rich, multiparametric outputs and rapid tractable characterization of activity and structure. We analyze a series of datasets of cytoskeleton networks and cell monolayers to demonstrate the ability of BARCODE to accelerate and streamline screening and analysis, reveal unexpected correlations and emergence, and enable broad non-expert data access, comparison, and sharing.