Article ID: | iaor2009348 |
Country: | United Kingdom |
Volume: | 23 |
Start Page Number: | 162 |
End Page Number: | 168 |
Publication Date: | Jan 2007 |
Journal: | Bioinformatics |
Authors: | Kahveci Tamer, Zhang Xu |
Keywords: | graphs, heuristics |
We consider the problem of multiple alignment of protein sequences with the goal of achieving a large SP (Sum-of-Pairs) score. We introduce a new graph-based method. We name our method QOMA (Quasi-Optimal Multiple Alignment). QOMA starts with an initial alignment. It represents this alignment using a K-partite graph. It then improves the SP score of the initial alignment through local optimizations within a window that moves greedily on the alignment. QOMA uses two parameters to permit flexibility in time/accuracy trade off: (1) the size of the window for local optimization, (2) the sparsity of the K-partite graph.