title: Non-linear molecular pattern classification using molecular beacons with multiple targets.
abstract: In vitro pattern classification has been highlighted as an important future application of DNA computing. Previous work has demonstrated the feasibility of linear classifiers using DNA-based molecular computing. However, complex tasks require non-linear classification capability. Here we design a molecular beacon that can interact with multiple targets and experimentally shows that its fluorescent signals form a complex radial-basis function, enabling it to be used as a building block for non-linear molecular classification in vitro. The proposed method was successfully applied to solving artificial and real-world classification problems: XOR and microRNA expression patterns.
authors.affiliation: School of Computer Science and Engineering, Seoul National University, 599 Gwanak-ro, Gwanak-gu, Seoul 151-742, Republic of Korea.
authors.forename: In-Hee
authors.initials: IH
authors.lastname: Lee
authors.forename: Seung Hwan
authors.initials: SH
authors.lastname: Lee
authors.forename: Tai Hyun
authors.initials: TH
authors.lastname: Park
authors.forename: Byoung-Tak
authors.initials: BT
authors.lastname: Zhang
mesh_terms: D002965:Classification / Q000379:methods*; D039301:Computers, Molecular / Q000639:trends*; D005453:Fluorescence; D035683:MicroRNAs / Q000145:classification / Q000235:genetics / Q000378:metabolism*; D008962:Models, Theoretical
chemical_list: D035683:MicroRNAs
keywords: Biological data analysis; DNA computing; Molecular beacons; Molecular pattern classification; Non-linear classification