Publication Date

2008

Degree Type

Master's Project

Degree Name

Master of Science (MS)

Department

Computer Science

Abstract

With the large amount of biological data generated due to DNA sequencing of various organisms, it is becoming necessary to identify techniques that can help in finding useful information amongst all the data. Finding motifs involves determining meaningful short sequences that may be repeated over many sequences in various species. Various approaches for the motif discovery problem have been proposed in the literature. One method suggests using genetic algorithms. In this project, an evolutionary approach for motif discovery has been explored. The population is clustered during every generation of the algorithm and then evolved locally within the clusters to allow the search space to maintain solution diversity.

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