Abstract:
There has been a number of research that has investigated the function of genes in a
sequence and how to synthesize genome sequence according to user specification. The
purpose of this thesis is to find a genome sequence which provides maximum amount
of flexibility and independence to biologists to run experiment with the sequence. Another
aim is to give opportunity for investigation of vaccine invention. To this end, we
propose to apply metaheuristics process for making a genome sequence uniquely prone
to enzymes.
We have applied a family of local and global search techniques to investigate which
search technique is better applicable for the problem under consideration. All implementation
of our algorithms are incorporated in the existing sequence design tool,
namely, PRESTO. Finally in our study, the process are simulated on a number of viral
sequences and the outcome is examined by statistical means. Through our extensive
experimental and statistical analysis, we have found that our local search techniques
perform better than the existing heuristics. Our findings also include that some global
search techniques do not perform as expected, even though they explores the search
space more. We have also found that multi-objective pareto optimization gives best output
in the current context.
