MSG: A Gap-Oriented Genetic Algorithm for Multiple Sequence Alignment

Author

Philip Heller, San Jose State University

Publication Date

2009

Degree Type

Master's Project

Degree Name

Master of Science (MS)

Department

Computer Science

Abstract

Traditional Multiple Sequence Alignment (MSA) Algorithms are deterministic. Genetic algorithms for protein MSA have been documented. However, these are not able to exceed in all cases the scores obtained by Clustal­W, the freely available de­facto standard. My solution, called “MSG”, places gaps rather than amino acids. The algorithm is multi­tribal, uses only a few very simple operators with adaptive frequencies, and jumpstarts one population from the Clustal­W solution. Results are reported for 14 data sets, on all of which MSG exceeds the Clustal­W score.

Recommended Citation

Heller, Philip, "MSG: A Gap-Oriented Genetic Algorithm for Multiple Sequence Alignment" (2009). Master's Projects. 141.
DOI: https://doi.org/10.31979/etd.m4nq-eg3k
https://scholarworks.sjsu.edu/etd_projects/141