International Journal of
Information and Education Technology

Abstract

Recent advent of the new high-throughput biological technologies has brought more challenges to the computer science community in terms of the amount and variety of biological data awaiting for analysis. Computationally intensive techniques such as pattern recognition and machine learning algorithms have been applied to extract knowledge from several biological domains ranging from genomics, proteomics to system biology and evolution process. Learning techniques applied to the computational biology are mostly in the category of classification. Therefore, the sequence analysis problem has to be formulated as classification task, which is quite difficult due to the unobvious one-to-one mapping of the problem. In this paper, we propose a different setting of sequence analysis formulation based on the nucleotide patterns using a constraint logic programming paradigm, in which the sequence alignment can be performed through pattern matching techniques. With available knowledge from the field of pattern mining, we can apply the well-established techniques within the new framework of constraint programming. However, to make the system efficiently work, we need a new set of constraint solver algorithms specifically designed for the sequence analysis problem. The design and implementation of such algorithms are thus the main focus of our research project. We propose in this paper the design of a constraint-based system for genomic sequence analysis including the algorithm for the constraint solver, a major part of the proposed system.