2009 | OriginalPaper | Chapter
Solving the Multiple Sequence Alignment Problem Using Prototype Optimization with Evolved Improvement Steps
Author : Jiří Kubalík
Published in: Adaptive and Natural Computing Algorithms
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
This paper deals with a Multiple Sequence Alignment problem, for which an implementation of the Prototype Optimization with Evolved Improvement Steps (POEMS) algorithm has been proposed. The key feature of the POEMS is that it takes some initial solution, which is then iteratively improved by means of what we call evolved hypermutations. In this work, the POEMS is seeded with a solution provided by the Clustal X algorithm. Major result of the presented experiments was that the proposed POEMS implementation performs significantly better than the other two compared algorithms, which rely on random hypermutations only. Based on the carried out analyses we proposed two modifications of the POEMS algorithm that might further improve its performance.