A Quantum-inspired optimization Heuristic for the Multiple Sequence Alignment Problem in Bio-computing

Abstract

Data related to biology are characterized by large volume and requirements for enormous computational power. Biological sequences, either of proteins or DNA/RNA segments, can be large and usually need massive computations in order to discover relations and study particular properties. Aligning sequences is of great importance for various practical reasons. Multiple sequence alignment studies the problem of aligning several strings resulting in a complete alignment, a problem for which several different approaches exist. In this work, a novel heuristic method to progressively solve this problem is proposed using elements of quantum-inspired optimization. The proposed algorithm is described in detail and evaluated through simulations against other aligning methods. The experimental results seem promising for providing a good initial alignment, especially for the case of large sets of sequences.