Rapid DNA origami nanostructure detection and classification using the YOLOv5 deep convolutional neural network.

ABSTRACT: The intra-image identification of DNA structures is essential to rapid prototyping and quality control of self-assembled DNA origami scaffold systems. We postulate that the YOLO modern object detection platform commonly used for facial recognition can be applied to rapidly scour atomic force microscope (AFM) images for identifying correctly formed DNA nanostructures with high fidelity. To make this approach widely available, we use open-source software and provide a straightforward procedure for designing a tailored, intelligent identification platform which can easily be repurposed to fit arbitrary structural geometries beyond AFM images of DNA structures. Here, we describe methods to acquire and generate the necessary components to create this robust system. Beginning with DNA structure

SUBMITTER: Chiriboga M 

PROVIDER: S-EPMC8907326 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature