In vitro molecular pattern classification via DNA-based weighted-sum operation

Hee Woong Lim, Seung Hwan Lee, Kyung Ae Yang, Ji Youn Lee, Suk In Yoo, Tai Hyun Park, Byoung Tak Zhang

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


Recent progress in molecular computation suggests the possibility of pattern classification in vitro. Weighted sum is a primitive operation required by many pattern classification problems. Here we present a DNA-based molecular computation method for implementing the weighted-sum operation and its use for molecular pattern classification in a test tube. The weights of the classifier are encoded as the mixing ratios of the differentially labeled probe DNA molecules, which are competitively hybridized with the input-encoding target molecules to compute the decision boundary of classification. The computation result is detected by fluorescence signals. We experimentally verify the underlying weight encoding scheme and demonstrate successful discrimination of two-group labels of synthetic DNA mixture patterns. The method can be used for direct computation on biomolecular data in a liquid state.

Original languageEnglish
Pages (from-to)1-7
Number of pages7
Issue number1
StatePublished - Apr 2010

Bibliographical note

Funding Information:
This research was supported in part by the Ministry of Commerce, Industry, and Energy through the Molecular Evolutionary Computing (MEC) project, the Ministry of Education, Science, and Technology under the BK21-IT Program and Pioneer Project, and the Ministry of Science and Technology through the National Research Laboratory (NRL) Program. Yang was supported by the Korea Research Foundation Grant funded by the Korean Government (KRF-2008-532-C00031). The ICT at Seoul National University provided research facilities for this study.


  • Competitive hybridization
  • DNA computing
  • DNA-based weighted-sum operation
  • Molecular pattern classification


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