We present practical parallel algorithms using prefix computations for various problems that arise in pairwise comparison of biological sequences. We consider both constant and affine gap penalty functions, full-sequence and subsequence matching, and space-saving algorithms. The best known sequential algorithms solve these problems in O(mn) time and O(m + n) space, where m and n are the lengths...

We describe a new method of comparing sequences, based on the Needleman-Wunsch sequence alignment algorithm, which can detect similarities that are interrupted by insertions or deletions in either sequence. The sequences are compared by calculating for each pair of residues a score which represents the best local alignment bringing those residues into correspondence; smooth localisation is achi...

This paper explores the flexile flow lines where setup times are sequence- dependent. The optimization criterion is the minimization of total weighted completion time. We propose an iterated greedy algorithm (IGA) to tackle the problem. An experimental evaluation is conducted to evaluate the proposed algorithm and, then, the obtained results of IGA are compared against those of some other exist...

In this study, we propose a new dynamic warping algorithm for cyclic sequence comparison, which approximate the optimal solution efficiently. The comparison of two sequences, whose starting points are known, is performed by finding the optimal correspondence between their elements, which minimize the distance. If the sequences are cyclic and their starting points are not known, the alignment co...

Sequence comparison is a fundamental step in many important tasks in bioinformatics. Traditional algorithms for measuring approximation in sequence comparison are based on the notions of distance or similarity, and are generally computed through sequence alignment techniques. As circular genome structure is a common phenomenon in nature, a caveat of specialized alignment techniques for circular...

The main way of analyzing biological sequences is by comparing and aligning them to each other. It remains difficult, however, to compare modern multi-billionbase DNA data sets. The difficulty is caused by the nonuniform (oligo)nucleotide composition of these sequences, rather than their size per se. To solve this problem, we modified the standard seed-and-extend approach (e.g., BLAST) to use a...

The article surveys parameterized algorithms and complexities for computational tasks on biopolymer sequences, including the problems of longest common subsequence, shortest common supersequence, pairwise sequence alignment, multiple sequencing alignment, structure-sequence alignment, and structure-structure alignment. Algorithm techniques built on the structural-unit level, as well as on the r...

Biological sequence comparison is a time consuming task on a Von Neuman computer. The addition of dedicated hardware for parallelizing the comparison algorithms results in a reduction of several orders of magnitude in the execution time. This paper presents and compares different dedicated approaches, based on the parallelization of the algorithms on linear arrays of processors.

We have developed three computer programs for comparisons of protein and DNA sequences. They can be used to search sequence data bases, evaluate similarity scores, and identify periodic structures based on local sequence similarity. The FASTA program is a more sensitive derivative of the FASTP program, which can be used to search protein or DNA sequence data bases and can compare a protein sequ...

We give two parallel algorithms for sequence comparison on the Connection Machine 2 (CM2). The specific comparison measure we compute is the erfif distance: given a finite alphabet £ and two input sequences X £ £ + and Y £ E + the edit distance Y ) is the minimum cost of transforming X into Y via a series of weighted insertions, deletions, and substitutions of characters. The edit distance comp...