Chin Francis Y, Ho N L, Lam T W, Wong Prudence W, Chan M Y
Department of Computer Science and Information Systems, The University of Hong Kong, Hong Kong.
Proc IEEE Comput Soc Bioinform Conf. 2003;2:337-46.
The Constrained Multiple Sequence Alignment problem is to align a set of sequences subject to a given constrained sequence, which arises from some knowledge of the structure of the sequences. This paper presents new algorithms for this problem, which are more efficient in terms of time and space (memory) than the previous algorithms [14], and with a worst-case guarantee on the quality of the alignment. Saving the space requirement by a quadratic factor is particularly significant as the previous O(n(4))-space algorithm has limited application due to its huge memory requirement. Experiments on real data sets confirm that our new algorithms show improvements in both alignment quality and resource requirements.
约束多序列比对问题是在给定约束序列的情况下对一组序列进行比对,该约束序列源自对序列结构的一些了解。本文提出了解决此问题的新算法,这些算法在时间和空间(内存)方面比以前的算法[14]更高效,并且在比对质量上有最坏情况保证。将空间需求节省二次方因子尤为重要,因为先前的O(n(4))空间算法由于其巨大的内存需求而应用有限。在真实数据集上的实验证实,我们的新算法在比对质量和资源需求方面都有改进。