Large Grain Size Stochastic Optimization Alignment

DNA sequence alignment is a critical step in identifying homology between organisms. The most widely used alignment program, ClustalW, is known to suffer from the local minima problem, where suboptimal guide trees produce incorrect gap insertions. The optimization alignment approach, has been shown to be effective in combining alignment and phylogenetic search in order to avoid the problems associated with poor guide trees. The optimization alignment algorithm operates at a small grain size with alignment occurring as each tree is searched, but wastes time producing multiple sequence alignments for suboptimal trees. This research develops and analyzes a large grain size algorithm for optimization alignment that iterates through steps of alignment and phylogeny search, thus improving the quality of guide trees used for computation of multiple sequence alignments and eliminating computation of multiple sequence alignments for sub-optimal guide trees. Local minima are avoided by the use ...

• Type: Conference
• Year: 2006
• Where: BIBE
• Authors: Perry Ridge, Hyrum Carroll, Dan Sneddon, Mark J. Clement, Quinn Snell
• Keywords: BIBE 2006, Bioinformatics, Multiple Sequence Alignments, Optimization Alignment, Sequence Alignments