一种基于Summary的改进型BLASTN算法

BLASTN Arithmetic Based on Summary Improvement

BLASTN是生物信息学实验中常用的局部相似性搜索软件。为此,提出了一种以BloomFilter为基础的算法,用于对BLASTN中的SeedFinding进行改进,以提高BLASTN的整体效率。该算法对原数据库文件制作Summary,在搜索过程中通过查询Summary以回避大量无效的匹配工作,并对算法的各方面进行分析,给出测试结果。

BLASTN is one of the most frequently used local alignment search tool in bioinformatics computing. This paper introduces a new algorithm, which is based on Bloom Filter algorithm, of Seed Finding in BLASTN. It improves the performance of BLASTN by building Summary for the sequence-database. According to the Summary, a lot of fruitless work can be avoided during the pattern-searching. The paper gives detail analysis on the new algorithm. Test results are also shown.