Gene prediction with a hidden Markov model and a new intron submodel
Gene prediction with a hidden Markov model and a new intron submodel
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DOI：
10.1093/bioinformatics/btg1080
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发表时间：
2003-09-01
期刊：
影响因子：
5.8
通讯作者：
Waack, Stephan
中科院分区：
文献类型：
--
作者：
Stanke, Mario;Waack, Stephan
动机：通过计算方法在真核生物DNA序列中寻找基因的问题仍未得到令人满意的解决。基因发现程序在短的基因组序列上已达到相对较高的准确性，但在其中基因数量未知的较长序列上表现不佳。在此情况下，现有程序往往会预测出许多假外显子。
结果：我们开发了一种新程序AUGUSTUS，用于真核生物基因组中蛋白质编码基因的从头预测。该程序基于隐马尔可夫模型，并整合了许多已知的方法和子模型。它采用了一种新的内含子长度建模方式。我们使用了一种新的供体剪接位点模型，一种在供体剪接位点模型正上游的短区域的新模型，该模型考虑了阅读框，并应用了一种能更好地进行依赖于GC含量的参数估计的方法。与我们所比较的从头基因预测程序相比，AUGUSTUS在较长序列上能更准确地预测出更多的人类和果蝇基因，同时特异性更高。
可用性：AUGUSTUS的网络界面和可执行程序位于http://augustus.gobics.de。
补充信息：用于测试和训练的数据集可在http://augustus.gobics.de/datasets/获取。
联系人：mstanke@gwdg.de
Motivation: The problem of finding the genes in eukaryotic DNA sequences by computational methods is still not satisfactorily solved. Gene finding programs have achieved relatively high accuracy on short genomic sequences but do not perform well on longer sequences with an unknown number of genes in them. Here existing programs tend to predict many false exons.Results: We have developed a new program, AUGUSTUS, for the ab initio prediction of protein coding genes in eukaryotic genomes. The program is based on a Hidden Markov Model and integrates a number of known methods and submodels. It employs a new way of modeling intron lengths. We use a new donor splice site model, a new model for a short region directly upstream of the donor splice site model that takes the reading frame into account and apply a method that allows better GC-content dependent parameter estimation. AUGUSTUS predicts on longer sequences far more human and drosophila genes accurately than the ab initio gene prediction programs we compared it with, while at the same time being more specific.Availability: A web interface for AUGUSTUS and the executable program are located at http://augustus.gobics.de.Supplementary Information: The datasets used for testing and training are available at http://augustus.gobics.de/datasets/Contact: mstanke@ gwdg.de