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XRate:一种用于系统发育语法的快速原型制作、训练和注释工具。

XRate: a fast prototyping, training and annotation tool for phylo-grammars.

作者信息

Klosterman Peter S, Uzilov Andrew V, Bendaña Yuri R, Bradley Robert K, Chao Sharon, Kosiol Carolin, Goldman Nick, Holmes Ian

机构信息

Department of Bioengineering, University of California, Berkeley CA, USA.

出版信息

BMC Bioinformatics. 2006 Oct 3;7:428. doi: 10.1186/1471-2105-7-428.

Abstract

BACKGROUND

Recent years have seen the emergence of genome annotation methods based on the phylo-grammar, a probabilistic model combining continuous-time Markov chains and stochastic grammars. Previously, phylo-grammars have required considerable effort to implement, limiting their adoption by computational biologists.

RESULTS

We have developed an open source software tool, xrate, for working with reversible, irreversible or parametric substitution models combined with stochastic context-free grammars. xrate efficiently estimates maximum-likelihood parameters and phylogenetic trees using a novel "phylo-EM" algorithm that we describe. The grammar is specified in an external configuration file, allowing users to design new grammars, estimate rate parameters from training data and annotate multiple sequence alignments without the need to recompile code from source. We have used xrate to measure codon substitution rates and predict protein and RNA secondary structures.

CONCLUSION

Our results demonstrate that xrate estimates biologically meaningful rates and makes predictions whose accuracy is comparable to that of more specialized tools.

摘要

背景

近年来,基于系统发育语法出现了基因组注释方法,这是一种结合连续时间马尔可夫链和随机语法的概率模型。以前,实现系统发育语法需要付出相当大的努力,限制了计算生物学家对其的采用。

结果

我们开发了一个开源软件工具xrate,用于处理与随机上下文无关语法相结合的可逆、不可逆或参数替换模型。xrate使用我们描述的一种新颖的“系统发育期望最大化(phylo-EM)”算法有效地估计最大似然参数和系统发育树。语法在外部配置文件中指定,允许用户设计新的语法,从训练数据估计速率参数,并注释多序列比对,而无需从源代码重新编译代码。我们已经使用xrate来测量密码子替换率并预测蛋白质和RNA二级结构。

结论

我们的结果表明,xrate估计具有生物学意义的速率,并做出准确性与更专业工具相当的预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f1b/1622757/880a2c0a6e3b/1471-2105-7-428-1.jpg

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