Schneider Georg, Wildpaner Michael, Sirota Fernanda L, Maurer-Stroh Sebastian, Eisenhaber Birgit, Eisenhaber Frank
Bioinformatics Institute, Agency for Science, Technology, and Research, Singapore.
Methods Mol Biol. 2010;609:257-67. doi: 10.1007/978-1-60327-241-4_15.
Given the amount of sequence data available today, in silico function prediction, which often includes detecting distant evolutionary relationships, requires sophisticated bioinformatic workflows. The algorithms behind these workflows exhibit complex data structures; they need the ability to spawn subtasks and tend to demand large amounts of resources. Performing sequence analytic tasks by manually invoking individual function prediction algorithms having to transform between differing input and output formats has become increasingly obsolete. After a period of linking individual predictors using ad hoc scripts, a number of integrated platforms are finally emerging. We present the ANNOTATOR software environment as an advanced example of such a platform.
鉴于如今可用的序列数据量,计算机模拟功能预测(通常包括检测远缘进化关系)需要复杂的生物信息学工作流程。这些工作流程背后的算法呈现出复杂的数据结构;它们需要具备生成子任务的能力,并且往往需要大量资源。通过手动调用单个功能预测算法来执行序列分析任务,且必须在不同的输入和输出格式之间进行转换,这种做法已越来越过时。在经历了一段使用临时脚本链接各个预测器的时期后,一些集成平台终于应运而生。我们将ANNOTATOR软件环境作为此类平台的一个先进示例进行介绍。