|We consider the problem of multiple sequence alignment: given k sequences of length at most n and a certain scoring function, nd an alignment that minimizes the corresponding \sum of pairs" distance score. We generalize the divide-and-conquer technique described in 1,2], and present new ideas on how to use eecient search strategies for saving computer memory and accelerating the procedure for ...

The Sequence Alignment Benchmark (SABmark) provides sets of multiple alignment problems derived from the SCOP classification. These sets, Twilight Zone and Superfamilies, both cover the entire known fold space using sequences with very low to low, and low to intermediate similarity, respectively. In addition, each set has an alternate version in which unalignable but apparently similar sequence...

Incorporating secondary structure information into the alignment process improves the quality of RNA sequence alignments. Instead of using fixed weighting parameters, sequence and structure components can be treated as different objectives and optimized simultaneously. The result is not a single, but a Pareto-set of equally optimal solutions, which all represent different possible weighting par...

This chapter is a brief introduction to two important statistical methods— maximum likelihood estimation and hypothesis testing. We shall show how to use these methods to test the biological sequence models developed in previous chapters against experimental data. We shall also show how hypothesis testing ideas inspire scoring methods for sequence alignment. denote the outcome of an experiment ...

This review focuses on recent trends in multiple sequence alignment tools. It describes the latest algorithmic improvements including the extension of consistency-based methods to the problem of template-based multiple sequence alignments. Some results are presented suggesting that template-based methods are significantly more accurate than simpler alternative methods. The validation of existin...