Comparative homology agreement search: An effective combination of homology-search methods
Comparative homology agreement search: An effective combination of homology-search methods
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DOI：
10.1073/pnas.0405612101
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发表时间：
2004-09-21
影响因子：
11.1
通讯作者：
Fuellen, G
中科院分区：
文献类型：
--
作者：
Alam, I;Dress, A;Fuellen, G
人们已经开发了许多方法来在数据库中搜索蛋白质家族的同源成员，如果只使用一种方法而忽略其他方法，则结果和结论的可靠性可能会受到影响。在这里，我们介绍了一个通用的方案，结合这些方法。基于此方案，我们实现了一种称为比较同源一致性搜索（CHASE）的工具，该工具集成了不同的搜索策略以获得组合的“E值”。“我们的研究结果表明，整合不同策略的共识方法很容易胜过其任何组件算法。更具体地，基于蛋白质结构分类数据库的评估揭示，平均而言，在搜索远亲同源物（即，同一超家族但不是同一家族的成员，这是一项非常困难的任务），仅接受10个假阳性，而单个方法获得28- 38%的覆盖率。
Many methods have been developed to search for homologous members of a protein family in databases, and the reliability of results and conclusions may be compromised if only one method is used, neglecting the others. Here we introduce a general scheme for combining such methods. Based on this scheme, we implemented a tool called comparative homology agreement search (CHASE) that integrates different search strategies to obtain a combined "E value." Our results show that a consensus method integrating distinct strategies easily outperforms any of its component algorithms. More specifically, an evaluation based on the Structural Classification of Proteins database reveals that, on average, a coverage of 47% can be obtained in searches for distantly related homologues (i.e., members of the same superfamily but not the same family, which is a very difficult task), accepting only 10 false positives, whereas the individual methods obtain a coverage of 28-38%.