Powerful fusion: PSI-BLAST and consensus sequences.
Powerful fusion: PSI-BLAST and consensus sequences.
复制标题
强大的融合：PSI-BLAST 和共有序列。
DOI：
10.1093/bioinformatics/btn384
复制
发表时间：
2008-09-15
期刊：
影响因子：
5.8
通讯作者：
Rost, Burkhard
中科院分区：
文献类型：
--
作者：
Przybylski, Dariusz;Rost, Burkhard
动机：典型的PSI-BLAST搜索包括迭代扫描和大型序列数据库的对齐，在此期间，评分配置文件逐步建立和完善。这样的配置文件也可以存储并用于针对不同的序列数据库进行搜索。使用它来搜索一致的数据库，而不是本地序列，这是一个简单的附加组件，可以惊人地提高性能。这种改进是有代价的：我们假设随机对齐得分统计数据在原生序列和共识序列之间会有所不同。因此，基于psi - blast的对一致性序列的配置文件搜索可能会错误地估计对齐分数的统计显著性。此外，针对共识数据库的迭代搜索可能会失败。在这里，我们解决了这些挑战，试图利用PSI-BLAST和共识序列相结合的全部力量。结果：我们研究了不同类型共识序列的比对得分统计。总体而言，基于谱的一致性序列比对的评分分布参数与原生序列的评分分布参数存在显著差异。PSI-BLAST部分补偿了参数变化。我们已经确定了一个协议，以建立专门的共识序列，显着提高搜索灵敏度和保留分数分布参数。因此，PSI-BLAST配置文件可以用于搜索专门的共识序列，而不会牺牲统计显著性的估计。我们还提供了结果表明迭代PSI-BLAST搜索对共识序列可以很好地工作。总的来说，我们展示了如何使用一种非常流行和有效的方法来识别蛋白质序列之间更多的相关相似性。可用性：http://www.rostlab.org/services/consensus/联系方式：dariusz@mit.edu
Motivation: A typical PSI-BLAST search consists of iterative scanning and alignment of a large sequence database during which a scoring profile is progressively built and refined. Such a profile can also be stored and used to search against a different database of sequences. Using it to search against a database of consensus rather than native sequences is a simple add-on that boosts performance surprisingly well. The improvement comes at a price: we hypothesized that random alignment score statistics would differ between native and consensus sequences. Thus PSI-BLAST-based profile searches against consensus sequences might incorrectly estimate statistical significance of alignment scores. In addition, iterative searches against consensus databases may fail. Here, we addressed these challenges in an attempt to harness the full power of the combination of PSI-BLAST and consensus sequences. Results: We studied alignment score statistics for various types of consensus sequences. In general, the score distribution parameters of profile-based consensus sequence alignments differed significantly from those derived for the native sequences. PSI-BLAST partially compensated for the parameter variation. We have identified a protocol for building specialized consensus sequences that significantly improved search sensitivity and preserved score distribution parameters. As a result, PSI-BLAST profiles can be used to search specialized consensus sequences without sacrificing estimates of statistical significance. We also provided results indicating that iterative PSI-BLAST searches against consensus sequences could work very well. Overall, we showed how a very popular and effective method could be used to identify significantly more relevant similarities among protein sequences. Availability: http://www.rostlab.org/services/consensus/ Contact: dariusz@mit.edu
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DOI：
10.1073/pnas.89.22.10915
发表时间：
1992-11-15
影响因子：
11.1
作者：
HENIKOFF, S;HENIKOFF, JG
通讯作者：
HENIKOFF, JG
影响因子：
14.9
作者：
Przybylski D;Rost B
通讯作者：
Rost B
Pfam：氏族、网络工具和服务。
影响因子：
14.9
作者：
Finn, Robert D.;Mistry, Jaina;Schuster-Bockler, Benjamin;Griffiths-Jones, Sam;Hollich, Volker;Lassmann, Timo;Moxon, Simon;Marshall, Mhairi;Khanna, Ajay;Durbin, Richard;Eddy, Sean R.;Sonnhammer, Erik L. L.;Bateman, Alex
通讯作者：
Bateman, Alex
影响因子：
5.8
作者：
Li, WZ;Jaroszewski, L;Godzik, A
通讯作者：
Godzik, A
影响因子：
3.4
作者：
Merkeev IV;Mironov AA
通讯作者：
Mironov AA