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

Abstract

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.