Title :
Global pairwise sequence alignment using Hidden Markov Models applied through different scoring schemes
Author :
Duran, Metin ; Bucak, Ihsan Omur
Author_Institution :
Fatih Univ., Buyukcekmece, Turkey
Abstract :
Hidden Markov Method in Bioinformatics is very popular since it proposed for the sequence analysis. This statistical method can be used from pairwise sequence alignment to database search. In this study, a global pairwise sequence alignment and database search using Hidden Markov Method are implemented. Although that can be solved by Dynamic Programming, the latter poses such a weakness that eventually leads to an excessive memory usage once all the possibilities are tried. Two different models are used to build Hidden Markov Model. The first one is untrimmed model and second is trimmed model. Additionally these models are compared through different scoring schemes.
Keywords :
bioinformatics; database management systems; dynamic programming; hidden Markov models; statistical analysis; bioinformatics; database search; dynamic programming; global pairwise sequence alignment; hidden Markov model; memory usage; scoring scheme; sequence analysis; statistical method; Analytical models; Bioinformatics; Biological system modeling; Computational modeling; Dynamic programming; Portable computers;
Conference_Titel :
Biomedical and Health Informatics (BHI), 2012 IEEE-EMBS International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4577-2176-2
Electronic_ISBN :
978-1-4577-2175-5
DOI :
10.1109/BHI.2012.6211743