DNA computing hardware design and application to multiclass cancer data

Abstract

DNA computing-inspired pattern classification based on the hypernetwork model is a novel approach to pattern classification problems. The hypernetwork model has been shown to be a powerful tool for analysis of gene expression data. However, the ordinary hypernetwork model has limitations, such as using only binary data and operating sequentially. In this paper, we propose an improved method to process four-level data and to implement a hardware circuit for DNA computing-inspired pattern classifier. We show simulation results of multi-class cancer classification from the DNA microarray data for performance evaluation. Experiments show competitive diagnosis results over other conventional machine learning algorithms. Our four-level data approach also results stable and improved performance over the ordinary hypernetwork model. © 2009 Springer Berlin Heidelberg.