A hybrid genetic search for multiple sequence alignment

This paper proposes a hybrid genetic algorithm for multiple sequence alignment. The algorithm evolves guide sequences and aligns input sequences based on the guide sequences. It also embeds a local search heuristic to search the problem space effectively. In the experiments for various data sets, the proposed algorithm showed the performance comparable to existing algorithms. Categories and Subject Descriptors J.3 [Life and medical sciences]: Biology and genetics, Medical information systems; F.2.2 [Nonnumerical algorithms and problems]: Sorting and searching General Terms Algorithms Keywords Bioinformatics, genetic algorithms, local search, multiple sequence alignment

• Type: Conference
• Year: 2006
• Where: GECCO
• Authors: Seung-Hyun Moon, Sung-Soon Choi, Byung Ro Moon
• Keywords: Algorithms, GECCO 2006, Genetic Algorithms, Multiple Sequence Alignment, Optimization