Machine Learning Aids Classification and Discrimination of Noncanonical DNA Folding Motifs by an Arrayed Host:Guest Sensing System
Junyi Chen, Adam D. Gill, Briana L. Hickey, Ziting Gao, Xinping Cui, Richard J. Hooley, Wenwan Zhong
Abstract
An arrayed host:guest fluorescence sensor system can discriminate among and classify multiple different noncanonical DNA structures by exploiting selective molecular recognition. The sensor is highly selective and can discriminate between folds as similar as native G-quadruplexes and those with bulges or vacancies. The host and guest can form heteroternary complexes with DNA strands, with the host acting as mediator between the DNA and dye, modulating the emission. By applying machine learning algorithms to the sensing data, prediction of the folding state of unknown DNA strands is possible with high fidelity.
Topics & Concepts
ChemistryDNAFolding (DSP implementation)Host (biology)FidelityHigh fidelityComputational biologyFluorescenceNanotechnologyBiophysicsGeneticsComputer sciencePhysicsBiochemistryBiologyEngineeringElectrical engineeringQuantum mechanicsAcousticsTelecommunicationsMaterials scienceAdvanced biosensing and bioanalysis techniquesDNA and Nucleic Acid ChemistryBacteriophages and microbial interactions