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Using Multiple Alignments to Improve Gene Prediction

机译:使用多重比对改善基因预测

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摘要

The multiple species de novo gene prediction problem can be stated as follows: given an alignment of genomic sequences from two or more organisms, predict the location and structure of all protein-coding genes in one or more of the sequences. Here, we present a new system, N-SCAN (a.k.a. TWINSCAN 3.0), for addressing this problem. N-SCAN has the ability to model dependencies between the aligned sequences, context-dependent substitution rates, and insertions and deletions in the sequences. An implementation of N-SCAN was created and used to generate predictions for the entire human genome. An analysis of the predictions reveals that N-SCAN's predictive accuracy in human exceeds that of all previously published whole-genome de novo gene predictors. In addition, predictions were generated for the genome of the fruit fly Drosophila melanogaster to demonstrate the applicability of N-SCAN to invertebrate gene prediction.
机译:从头开始的多物种基因预测问题可以描述如下:给定来自两个或多个生物的基因组序列的比对,预测一个或多个序列中所有蛋白质编码基因的位置和结构。在这里,我们提出了一个新系统N-SCAN(又名TWINSCAN 3.0)来解决这个问题。 N-SCAN具有对比对序列之间的依赖性,上下文相关的替换率以及序列中的插入和缺失进行建模的能力。创建了N-SCAN的实现,并用于生成整个人类基因组的预测。对这些预测的分析表明,N-SCAN在人类中的预测准确性超过了所有先前发表的全基因组从头基因预测因子。此外,对果蝇果蝇的基因组进行了预测,以证明N-SCAN在无脊椎动物基因预测中的适用性。

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