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引用次数: 7
摘要
本文研究了如何为蛋白质序列建立持久索引结构以支持近似匹配的问题。后缀树已被提出作为索引序列数据库的解决方案,并已用于组织DNA序列(Hunt et al.(2001))。不幸的是,它受到“内存瓶颈”问题的困扰,这使得它无法有效地应用于大型数据库。对于蛋白质数据库,由于每个节点的扇出更大,性能甚至会进一步下降。在这里,我们采用一种称为BASS-tree的索引结构来支持大型蛋白质数据库在亚线性时间内的近似匹配。我们称这种索引方法为序列近似匹配索引方法。近似匹配的搜索可以适当地定向到数据库中具有高匹配潜力的部分。我们的实验表明,与BLAST算法和后缀树等替代方法相比,潜在的性能改进是一个数量级。
Accelerating approximate subsequence search on large protein sequence databases
In this paper, we study the problem on how to build a persistent index structure for protein sequences to support approximate match. The suffix tree has been proposed as a solution to index sequence database and has been deployed on organizing DNA sequences (Hunt et al. (2001)). Unfortunately, it suffers from the problem of "memory bottleneck" that prevents it from being applied efficiently to a large database. The performance even degrades further for protein database due to a larger fanout at each node. Here, we employ an indexing structure, called BASS-tree, to support approximate match in sublinear time on a large protein database. We call this indexing method the sequence approximate match index method. The search of approximate matches can be properly directed to the portion in the database with a high potential of matching quickly. It is demonstrated in our experiments that the potential performance improvement is in an order of magnitude over alternative methods such as the BLAST algorithm and the suffix tree.