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Simultaneous gene finding in multiple genomes

机译:在多个基因组中同时发现基因

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Motivation: As the tree of life is populated with sequenced genomes ever more densely, the new challenge is the accurate and consistent annotation of entire clades of genomes. We address this problem with a new approach to comparative gene finding that takes a multiple genome alignment of closely related species and simultaneously predicts the location and structure of protein-coding genes in all input genomes, thereby exploiting negative selection and sequence conservation. The model prefers potential gene structures in the different genomes that are in agreement with each other, or-if not-where the exon gains and losses are plausible given the species tree. We formulate the multi-species gene finding problem as a binary labeling problem on a graph. The resulting optimization problem is NP hard, but can be efficiently approximated using a subgradient-based dual decomposition approach.
机译:动机:随着生命之树越来越密集地排列着测序的基因组,新的挑战是对整个基因组进化枝的准确和一致的注释。我们用一种比较基因发现的新方法解决了这个问题,该方法采用了紧密相关物种的多基因组比对并同时预测了所有输入基因组中蛋白质编码基因的位置和结构,从而利用了阴性选择和序列保守性。该模型倾向于在彼此一致的不同基因组中的潜在基因结构,或者如果不是这样的话,则在给定物种树的情况下外显子的得失是合理的。我们将多物种基因发现问题公式化为图形上的二进制标记问题。产生的优化问题是NP难题,但可以使用基于子梯度的对偶分解方法有效地近似。

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