http://swrc.ontoware.org/ontology#Article
A Modified Algorithm for Sequence Alignment Using Ant Colony System
en
Original Papers
Department of Computer Science and Systems Engineering, Muroran Institute of Technology
Department of Computer Science and Systems Engineering, Muroran Institute of Technology
Ai Mikami
Jianming Shi
In this study, we use the Ant Colony System (ACS) to develop a heuristic algorithm for sequence alignment. This algorithm is certainly an improvement on ACS-MultiAlignment, which was proposed in 2005 for predicting major histocompatibility complex (MHC) class II binders. The numerical experiments indicate that this algorithm is as much as 2,900 times faster than the original ACS-MultiAlignment algorithm. We also compare this algorithm to the other approaches such as Gibbs sampling algorithm using numerical experiments. The results show that our algorithm finds the best value prompter than Gibbs approach.
In this study, we use the Ant Colony System (ACS) to develop a heuristic algorithm for sequence alignment. This algorithm is certainly an improvement on ACS-MultiAlignment, which was proposed in 2005 for predicting major histocompatibility complex (MHC) class II binders. The numerical experiments indicate that this algorithm is as much as 2,900 times faster than the original ACS-MultiAlignment algorithm. We also compare this algorithm to the other approaches such as Gibbs sampling algorithm using numerical experiments. The results show that our algorithm finds the best value prompter than Gibbs approach.
AA12177013
IPSJ Transactions on Bioinformatics （TBIO）
2
63-73
2009-05-25
1882-6679