GAZE: A generic framework for the integration of gene-prediction data by dynamic programming
GAZE: A generic framework for the integration of gene-prediction data by dynamic programming
复制标题
DOI：
10.1101/gr.149502
复制
发表时间：
2002-09-01
期刊：
影响因子：
7
通讯作者：
Durbin, R
中科院分区：
文献类型：
--
作者：
Howe, KL;Chothia, T;Durbin, R
我们描述了一种方法（在一个程序中实现，GAZE），用于将单个基因成分（特征）的任意证据组装成完整基因结构的预测。我们的系统是通用的，因为特征本身，以及用于验证和评分潜在装配的基因结构模型，都是系统外部的，由用户提供。GAZE采用动态规划算法，根据每个输入特征属于某个基因的模型和后验概率，获得得分最高的基因结构。一种新颖的剪枝策略保证了算法的运行时间在序列长度上是有效线性的。为了展示我们的系统在将额外证据纳入基因预测过程中的灵活性，我们展示了如何使用它来表示非标准基因结构（以秀丽隐杆线虫反式剪合基因的形式），并利用相似性信息（以表达序列标记的形式），同时不需要更改底层软件。GAZE可以在http://www上找到。sanger.ac.uk /Software/ analysis/ GAZE。
We describe a method (implemented ill a program, GAZE) for assembling arbitrary evidence for individual gene components (features) into predictions of complete gene structures. Our system is generic in that both the features themselves, and the model of gene structure against which potential assemblies are validated and scored, are external to the system and Supplied by the user. GAZE uses a dynamic programming algorithm to obtain the highest scoring gene structure according to the model and posterior probabilities that each input feature is part of a gene. A novel pruning strategy ensures that the algorithm has a run-time effectively linear in sequence length. To demonstrate the flexibility Of Our system ill the incorporation of additional evidence into the gene prediction process, we show how it can be used to both represent nonstandard gene structures (ill the form of trans-spliced genes in Caenorhabditis elegans), and make use of similarity information (in the form of Expressed Sequence Tag alignments), while requiring no change to the underlying software. GAZE is available at http://www. sanger.ac.uk /Software/ analysis/ GAZE.