An evolutionary progressive multiple sequence alignment

Abstract This paper presents a new evolutionary method, namely, a Two Phase evolutionary algorithm for multiple sequence alignments. This method is composed of different types of evolutionary algorithms, that is, an evolutionary progressive multiple sequence alignment method (abbreviated to ET) and Sequence Alignment by Genetic Algorithm (abbreviated to SAGA). The former is employed to obtain efficiently good quality of multiple alignments and the latter to improve them much better. The basic idea was obtained from analysis of the characteristics of the two evolutionary methods, that is, the ET and SAGA can compensate each other’s weak points. Experimental evaluation shows that the proposed Two Phase method can generate good quality of multiple alignments.

• Type: Conference
• Year: 2007
• Where: CEC
• Authors: Farhana Naznin, Morikazu Nakamura, Takeo Okazaki, Yumiko Nakajima
• Keywords: Artificial Intelligence, CEC 2007, Evolutionary, Evolutionary Algorithms, Multiple Sequence Alignment