  DNA computing is an unconventional approach to computing that harnesses the
parallelism and information storage capabilities of DNA molecules. It has
emerged as a promising field with potential applications in solving a variety
of computationally complex problems. This paper explores a DNA computing
algorithm for Boolean matrix multiplication proposed by Nobuyuki et al. (2006)
using a computer simulation, inspired by similar work done in the past by
Obront (2021) for the DNA computing algorithm developed by Adleman (1994) for
solving the Hamiltonian path problem. We develop a Python program to simulate
the logical operations involved in the DNA-based Boolean matrix multiplication
algorithm. The simulation replicates the key steps of the algorithm, including
DNA sequence generation and hybridization, without imitating the physical
behaviour of the DNA molecules. It is intended to serve as a basic prototype
for larger, more comprehensive DNA computing simulators that can be used as
educational or research tools in the future. Through this work, we aim to
contribute to the understanding of DNA-based computing paradigms and their
potential advantages and trade-offs compared to conventional computing systems,
paving the way for future research and advancements in this emerging field.
