Predicting Binding Sites in the Mouse Genome

Yi Sun, M. Robinson, R. Adams, N. Davey, A. Rust
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引用次数: 3

Abstract

The identification of cis-regulatory binding sites in DNA in multicellular eukaryotes is a particularly difficult problem in computational biology. To obtain a full understanding of the complex machinery embodied in genetic regulatory networks it is necessary to know both the identity of the regulatory transcription factors together with the location of their binding sites in the genome. We show that using an SVM together with data sampling, to integrate the results of individual algorithms specialised for the prediction of binding site locations, can produce significant improvements upon the original algorithms applied to the mouse genome. These results make more tractable the expensive experimental procedure of actually verifying the predictions.
预测小鼠基因组中的结合位点
多细胞真核生物DNA顺式调控结合位点的鉴定是计算生物学中一个特别困难的问题。为了充分了解遗传调控网络中的复杂机制,有必要了解调控转录因子的身份及其在基因组中结合位点的位置。我们表明,将支持向量机与数据采样一起使用,整合专门用于预测结合位点位置的单个算法的结果,可以对应用于小鼠基因组的原始算法产生显着改进。这些结果使实际验证预测的昂贵实验过程更加容易处理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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