  In this paper, we present an optical computing method for string data
alignment applicable to genome information analysis. By applying moire
technique to spatial encoding patterns of deoxyribonucleic acid (DNA)
sequences, association information of the genome and the expressed phenotypes
could more effectively be extracted. Such moire fringes reveal occurrence of
matching, deletion and insertion between DNA sequences providing useful
visualized information for prediction of gene function and classification of
species. Furthermore, by applying a cylindrical lens, a new technique is
proposed to map two-dimensional (2D) association information to a
one-dimensional (1D) column of pixels, where each pixel in the column is
representative of superposition of all bright and dark pixels in the
corresponding row. By such a time-consuming preprocessing, local similarities
between two intended patterns can readily be found by just using a 1D array of
photodetectors and postprocessing could be performed on specified parts in the
initial 2D pattern. We also evaluate our proposed circular encoding adapted for
poor data alignment condition. Our simulation results together with
experimental implementation verify the effectiveness of our dynamic proposed
methods which significantly improve system parameters such as processing gain
and signal to noise ratio (SNR).
