title: Base motif recognition and design of DNA templates for fluorescent silver clusters by machine learning.
abstract: Discriminative base motifs within DNA templates for fluorescent silver clusters are identified using methods that combine large experimental data sets with machine learning tools for pattern recognition. Combining the discovery of certain multibase motifs important for determining fluorescence brightness with a generative algorithm, the probability of selecting DNA templates that stabilize fluorescent silver clusters is increased by a factor of >3.
authors.affiliation: Physics Department, UCSB, Santa Barbara, CA, 93106, USA.
authors.forename: Stacy M
authors.initials: SM
authors.lastname: Copp
authors.forename: Petko
authors.initials: P
authors.lastname: Bogdanov
authors.forename: Mark
authors.initials: M
authors.lastname: Debord
authors.forename: Ambuj
authors.initials: A
authors.lastname: Singh
authors.forename: Elisabeth
authors.initials: E
authors.lastname: Gwinn
mesh_terms: D001185:Artificial Intelligence; D001483:Base Sequence; D004247:DNA / Q000737:chemistry*; D005453:Fluorescence; D010363:Pattern Recognition, Automated / Q000379:methods*; D018030:Silver Compounds / Q000737:chemistry*; D013050:Spectrometry, Fluorescence
chemical_list: D018030:Silver Compounds; D004247:DNA
keywords: DNA nanotechnology; base motifs; fluorescent silver clusters; ligand-stabilized clusters; machine learning