title: ProbCons: Probabilistic consistency-based multiple sequence alignment.
abstract: To study gene evolution across a wide range of organisms, biologists need accurate tools for multiple sequence alignment of protein families. Obtaining accurate alignments, however, is a difficult computational problem because of not only the high computational cost but also the lack of proper objective functions for measuring alignment quality. In this paper, we introduce probabilistic consistency, a novel scoring function for multiple sequence comparisons. We present ProbCons, a practical tool for progressive protein multiple sequence alignment based on probabilistic consistency, and evaluate its performance on several standard alignment benchmark data sets. On the BAliBASE, SABmark, and PREFAB benchmark alignment databases, ProbCons achieves statistically significant improvement over other leading methods while maintaining practical speed. ProbCons is publicly available as a Web resource.
authors.affiliation: Department of Computer Science, Stanford University, Stanford, California 94305, USA.
authors.forename: Chuong B
authors.initials: CB
authors.lastname: Do
authors.forename: Mahathi S P
authors.initials: MS
authors.lastname: Mahabhashyam
authors.forename: Michael
authors.initials: M
authors.lastname: Brudno
authors.forename: Serafim
authors.initials: S
authors.lastname: Batzoglou
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence / Q000235:genetics; D019985:Benchmarking / Q000379:methods / Q000706:statistics & numerical data; D019295:Computational Biology / Q000379:methods / Q000706:statistics & numerical data; D030562:Databases, Protein / Q000592:standards / Q000706:statistics & numerical data; D014644:Genetic Variation / Q000235:genetics; D008969:Molecular Sequence Data; D016415:Sequence Alignment / Q000379:methods* / Q000706:statistics & numerical data*; D012984:Software; D012986:Software Validation