Machine Learning-Assisted DNA Origami Shape Sorting Using Fingerprinting Nanosensors and Feature Engineering.

ABSTRACT: Reconfigurable DNA nanostructures have emerged as a promising research area with applications in drug delivery, molecular computing, biosensing, and stimuli-responsive soft nanomaterials. While significant progress has been made in creating novel DNA nanostructures and exploring their applications, comparatively little effort has focused on developing new methodologies to confirm their folding. Conventional imaging approaches typically rely on sophisticated microscopy techniques including atomic force and transmission electron microscopy. Alternative low-cost methods for verifying DNA nanostructure assembly and shape sorting are thus highly valuable. Here, we present a fingerprinting nanosensor array integrated with machine learning (ML) to distinguish between two DNA origami shapes (trian

SUBMITTER: Singha S 

PROVIDER: S-EPMC12856829 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature