Improvement in accuracy of multiple sequence alignment using novel group-to-group sequence alignment algorithm with piecewise li

Background: Multiple sequence alignment (MSA) is a useful tool in bioinformatics. Although many MSA algorithms have been developed, there is still room for improvement in accuracy and speed. In the alignment of a family of protein sequences, global MSA algorithms perform better than local ones in many cases, while local ones perform better than global ones when some sequences have long insertions or deletions (indels) relative to others. Many recent leading MSA algorithms have incorporated pairwise alignment information obtained from a mixture of sources into their scoring system to improve accuracy of alignment containing long indels. Results: We propose a novel group-to-group sequence alignment algorithm that uses a piecewise linear gap cost. We developed a program called PRIME, which employs our proposed algorithm to optimize the well-defined sum-of-pairs score. PRIME stands for Profile-based Randomized Iteration MEthod. We evaluated PRIME and some recent MSA programs using BAliBAS...

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: Shinsuke Yamada, Osamu Gotoh, Hayato Yamana
• Keywords: BMCBI 2006, MSA Algorithms, Multiple Sequence Alignment, Sequence Alignment