title: QOMA: quasi-optimal multiple alignment of protein sequences.
abstract: BACKGROUND
  We consider the problem of multiple alignment of protein sequences with the goal of achieving a large SP (Sum-of-Pairs) score.
  
  
  RESULTS
  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. Unlike traditional progressive methods, QOMA is independent of the order of sequences. The experimental results on BAliBASE benchmarks show that QOMA produces higher SP score than the existing tools including ClustalW, Probcons, Muscle, T-Coffee and DCA. The difference is more significant for distant proteins.
  
  
  BACKGROUND
  The software is available from the authors upon request.
authors.affiliation: Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611, USA.
authors.forename: Xu
authors.initials: X
authors.lastname: Zhang
authors.forename: Tamer
authors.initials: T
authors.lastname: Kahveci
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D017124:Conserved Sequence; D008969:Molecular Sequence Data; D011506:Proteins / Q000737:chemistry*; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D017386:Sequence Homology, Amino Acid; D012984:Software
chemical_list: D011506:Proteins