A NICHED PARETO GENETIC ALGORITHM - For Multiple Sequence Alignment Optimization

Fernando José Mateus da Silva, Juan Manuel Sánchez Pérez, Juan Antonio Gómez Pulido, Miguel A. Vega Rodríguez

2010

Abstract

The alignment of molecular sequences is a recurring task in bioinformatics, but it is not a trivial problem. The size and complexity of the search space involved difficult the task of finding the optimal alignment of a set of sequences. Due to its adaptive capacity in large and complex spaces, Genetic Algorithms emerge as good candidates for this problem. Although they are often used in single objective domains, its use in multidimensional problems allows finding a set of solutions which provide the best possible optimization of the objectives – the Pareto front. Niching methods, such as sharing, distribute these solutions in space, maximizing their diversity along the front. We present a niched Pareto Genetic Algorithm for sequence alignment which we have tested with six BAliBASE alignments, taking conclusions regarding population evolution and quality of the final results. Whereas methods for finding the best alignment are mathematical, not biological, having a set of solutions which facilitate experts’ choice, is a possibility to consider.

Paper Citation

in Harvard Style

José Mateus da Silva F., Manuel Sánchez Pérez J., Antonio Gómez Pulido J. and A. Vega Rodríguez M. (2010). A NICHED PARETO GENETIC ALGORITHM - For Multiple Sequence Alignment Optimization . In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-674-021-4, pages 323-329. DOI: 10.5220/0002729303230329

in Bibtex Style

@conference{icaart10,
author={Fernando José Mateus da Silva and Juan Manuel Sánchez Pérez and Juan Antonio Gómez Pulido and Miguel A. Vega Rodríguez},
title={A NICHED PARETO GENETIC ALGORITHM - For Multiple Sequence Alignment Optimization},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2010},
pages={323-329},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002729303230329},
isbn={978-989-674-021-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - A NICHED PARETO GENETIC ALGORITHM - For Multiple Sequence Alignment Optimization
SN - 978-989-674-021-4
AU - José Mateus da Silva F.
AU - Manuel Sánchez Pérez J.
AU - Antonio Gómez Pulido J.
AU - A. Vega Rodríguez M.
PY - 2010
SP - 323
EP - 329
DO - 10.5220/0002729303230329