—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.
—Genomic sequence analysis, constraint-based
system, constraint solver algorithm, constraint programming.
The authors are with the School of Computer Engineering. They are also
with Data Engineering Research Unit, Suranaree University of Technology,
111 University Avenue, Muang District, Nakhon Ratchasima 30000,
Thailand (e-mail: firstname.lastname@example.org, kittisakThailand@gmail.com).
Cite: Nittaya Kerdprasop and Kittisak Kerdprasop, "Constraint-Based System for Genomic Analysis," International Journal of Information and Education Technology vol. 5, no. 2, pp. 119-123, 2015.