自然基因组在DCJ-indel模型中的微小简约。

IF 0.9 4区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Daniel Doerr, Cedric Chauve
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引用次数: 2

摘要

小简约问题(Small Parsimony Problem, SPP)的目标是在给定的系统发育树的内部节点上找到基因顺序,从而使整个基因组沿着树枝的重排距离最小化。这个问题在大多数基因组重排模型中是难以解决的,特别是当考虑到基因复制和丢失时。在这项工作中,我们描述了一个整数线性规划算法来解决自然基因组的SPP,即包含保守的、唯一的和重复的标记的基因组。我们考虑的进化模型是DCJ-indel模型,包括双切和连接重排操作和基因组片段的插入和删除。我们在模拟数据上评估了我们的算法,并表明它能够在非常全面的进化模型中非常有效和准确地重建祖先基因顺序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Small parsimony for natural genomes in the DCJ-indel model.

The Small Parsimony Problem (SPP) aims at finding the gene orders at internal nodes of a given phylogenetic tree such that the overall genome rearrangement distance along the tree branches is minimized. This problem is intractable in most genome rearrangement models, especially when gene duplication and loss are considered. In this work, we describe an Integer Linear Program algorithm to solve the SPP for natural genomes, i.e. genomes that contain conserved, unique, and duplicated markers. The evolutionary model that we consider is the DCJ-indel model that includes the Double-Cut and Join rearrangement operation and the insertion and deletion of genome segments. We evaluate our algorithm on simulated data and show that it is able to reconstruct very efficiently and accurately ancestral gene orders in a very comprehensive evolutionary model.

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来源期刊
Journal of Bioinformatics and Computational Biology
Journal of Bioinformatics and Computational Biology MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
2.10
自引率
0.00%
发文量
57
期刊介绍: The Journal of Bioinformatics and Computational Biology aims to publish high quality, original research articles, expository tutorial papers and review papers as well as short, critical comments on technical issues associated with the analysis of cellular information. The research papers will be technical presentations of new assertions, discoveries and tools, intended for a narrower specialist community. The tutorials, reviews and critical commentary will be targeted at a broader readership of biologists who are interested in using computers but are not knowledgeable about scientific computing, and equally, computer scientists who have an interest in biology but are not familiar with current thrusts nor the language of biology. Such carefully chosen tutorials and articles should greatly accelerate the rate of entry of these new creative scientists into the field.
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