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序列比对搜索

Serial BLAST searching.

作者信息

Korf Ian

机构信息

The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK.

出版信息

Bioinformatics. 2003 Aug 12;19(12):1492-6. doi: 10.1093/bioinformatics/btg199.

Abstract

MOTIVATION

The translating BLAST algorithms are powerful tools for finding protein-coding genes because they identify amino acid similarities in nucleotide sequences. Unfortunately, these kinds of searches are computationally intensive and often represent bottlenecks in sequence analysis pipelines. Tuning parameters for speed can make the searches much faster, but one risks losing low-scoring alignments. However, high scoring alignments are relatively resistant to such changes in parameters, and this fact makes it possible to use a serial strategy where a fast, insensitive search is used to pre-screen a database for similar sequences, and a slow, sensitive search is used to produce the sequence alignments.

RESULTS

Serial BLAST searches improve both the speed and sensitivity.

摘要

动机

翻译后的BLAST算法是寻找蛋白质编码基因的强大工具,因为它们能识别核苷酸序列中的氨基酸相似性。不幸的是,这类搜索计算量很大,常常成为序列分析流程中的瓶颈。调整参数以提高速度能使搜索快得多,但存在丢失低得分比对的风险。然而,高得分比对相对而言对参数变化有抗性,这一事实使得可以采用一种串行策略,即先用快速、不敏感的搜索在数据库中预筛选相似序列,再用慢速、敏感的搜索来生成序列比对。

结果

串行BLAST搜索提高了速度和灵敏度。

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