BACKGROUND: A fundamental assumption of all widely-used multiple sequence 
alignment techniques is that the left- and right-most positions of the input 
sequences are relevant to the alignment. However, the position where a sequence 
starts or ends can be totally arbitrary due to a number of reasons: 
arbitrariness in the linearisation (sequencing) of a circular molecular 
structure; or inconsistencies introduced into sequence databases due to 
different linearisation standards. These scenarios are relevant, for instance, 
in the process of multiple sequence alignment of mitochondrial DNA, viroid, 
viral or other genomes, which have a circular molecular structure. A solution 
for these inconsistencies would be to identify a suitable rotation (cyclic 
shift) for each sequence; these refined sequences may in turn lead to improved 
multiple sequence alignments using the preferred multiple sequence alignment 
program.
RESULTS: We present MARS, a new heuristic method for improving Multiple circular 
sequence Alignment using Refined Sequences. MARS was implemented in the C++ 
programming language as a program to compute the rotations (cyclic shifts) 
required to best align a set of input sequences. Experimental results, using 
real and synthetic data, show that MARS improves the alignments, with respect to 
standard genetic measures and the inferred maximum-likelihood-based phylogenies, 
and outperforms state-of-the-art methods both in terms of accuracy and 
efficiency. Our results show, among others, that the average pairwise distance 
in the multiple sequence alignment of a dataset of widely-studied mitochondrial 
DNA sequences is reduced by around 5% when MARS is applied before a multiple 
sequence alignment is performed.
CONCLUSIONS: Analysing multiple sequences simultaneously is fundamental in 
biological research and multiple sequence alignment has been found to be a 
popular method for this task. Conventional alignment techniques cannot be used 
effectively when the position where sequences start is arbitrary. We present 
here a method, which can be used in conjunction with any multiple sequence 
alignment program, to address this problem effectively and efficiently.