Dynamic use of multiple parameter sets in sequence alignment

Dynamic use of multiple parameter sets in sequence alignment

The level of conservation between two homologous sequences often varies among sequence regions; functionally important domains are more conserved than the remaining regions. Thus, multiple parameter sets should be used in alignment of homologous sequences with a stringent parameter set for highly conserved regions and a moderate parameter set for weakly conserved regions. We describe an alignme...

Multiple Sequence Alignment Multiple Sequence Alignment

An algorithm for progressive multiple alignment of sequences with insertions " , 1. Introduction The problem of sequence alignment is to find the patterns of sequence conservation and similarity between pairs or sets of given sequences. In biological contexts, similarity between biological sequences usually amounts to either functional or structural similarities or divergence from a common ance...

Accuracy Estimation and Parameter Advising for Protein Multiple Sequence Alignment

Abstract We develop a novel and general approach to estimating the accuracy of multiple sequence alignments without knowledge of a reference alignment, and use our approach to address a new task that we call parameter advising: the problem of choosing values for alignment scoring function parameters from a given set of choices to maximize the accuracy of a computed alignment. For protein alignm...

Eliminating Dynamic Programming Bias in Multiple Sequence Alignment Algorithms

A New Dynamic Programming Algorithm for Multiple Sequence Alignment

Abstract. Multiple sequence alignment (MSA) is one of the most basic and central tasks for many studies in modern biology. In this paper, we present a new progressive alignment algorithm for this very difficult problem. Given two groups A and B of aligned sequences, this algorithm uses Dynamic Programming and the sum-of-pairs objective function to determine an optimal alignment C of A and B. Th...