A parallel combinatorial algorithm for subtle motifs.

In bioinformatics, motif finding is one of the most common problems. It is to locate recurring patterns in the sequence of nucleotides or amino acids. The main difficulty of the problem is that the patterns are not exact matches owing to biological mutations. It is NP-complete. Within the literature many solutions have been provided for this challenging problem. Nevertheless, they do not address certain subtleties. Among them, one is addressed by Hu (2003). In this paper, we propose a parallel combinatorial algorithm for subtle motif finding on a Shared Memory Multiprocessor model. We suggest a method of implementation for the same.

A novel generalized design methodology and realization of Boolean operations using DNA.

The biological deoxyribonucleic acid (DNA) strand has been increasingly seen as a promising computing unit. A new algorithm is formulated in this paper to design any DNA Boolean operator with molecular beacons (MBs) as its input. Boolean operators realized using the proposed design methodology is presented. The developed operators adopt a uniform representation for logical 0 and 1 for any Boolean operator. The Boolean operators designed in this work employ only a hybridization operation at each stage. Further, this paper for the first time brings out the realization of a binary adder and subtractor using molecular beacons. Simulation results of the DNA-based binary adder and subtractor are given to validate the design.