Non-linear molecular pattern classification using molecular beacons with multiple targets

In Hee Lee, Seung Hwan Lee, Tai Hyun Park, Byoung Tak Zhang

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


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.

Original languageEnglish
Pages (from-to)206-213
Number of pages8
Issue number3
StatePublished - Dec 2013

Bibliographical note

Funding Information:
This research was supported in part by the Ministry of Knowledge Economy (MKE) through the Molecular Evolutionary Computing (MEC) project, the National Research Foundation of Korea (NRF) grant funded by the Ministry of Education, Science & Technology (MEST) (No. 0421-20110032 ), and the BK21-IT Program. The ICT at Seoul National University provided research facilities for this study.


  • Biological data analysis
  • DNA computing
  • Molecular beacons
  • Molecular pattern classification
  • Non-linear classification


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