Recovering motifs from biased genomes: application of signal correction.
Recovering motifs from biased genomes: application of signal correction.
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DOI：
10.1093/nar/gkl676
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发表时间：
2006
影响因子：
14.9
通讯作者：
Schreiber, Mark
中科院分区：
文献类型：
--
作者：
Hasan, Samiul;Schreiber, Mark
在生物基序分析中，当背景符号分布有偏差时（例如，在DNA序列的情况下，高/低GC含量）会出现一个重大问题。这可能导致高估基序中编码的信息量。基序可以用信息理论（IT）来描述为一个信号。我们应用IT中的两个概念，扭曲和模式干扰（一种噪声），分别模拟基因组和密码子偏差。这种建模方法允许我们校正原始信号以恢复被成分偏置削弱的信号。校正后的信号更有可能被大分子从有偏差的背景中区分出来。我们应用这种校正技术来恢复核糖体结合位点（RBS）信号从现有的测序和注释的原核生物基因组具有不同的组成偏差。我们观察到，即使在这些偏差的极端情况下，线性校正也足以恢复信号。在校正这些信号后，进一步的比较基因组学研究成为可能。我们发现使用校正技术可以显著降低不同基因组的RBS信号频率矩阵之间的平均欧几里德距离。在这个减少的平均距离内，我们可以找到特定于类的RBS信号的例子。我们的结果对基于基序的预测具有启示意义，特别是关于可靠的基因组间模型参数的估计。
A significant problem in biological motif analysis arises when the background symbol distribution is biased (e.g. high/low GC content in the case of DNA sequences). This can lead to overestimation of the amount of information encoded in a motif. A motif can be depicted as a signal using information theory (IT). We apply two concepts from IT, distortion and patterned interference (a type of noise), to model genomic and codon bias respectively. This modeling approach allows us to correct a raw signal to recover signals that are weakened by compositional bias. The corrected signal is more likely to be discriminated from a biased background by a macromolecule. We apply this correction technique to recover ribosome-binding site (RBS) signals from available sequenced and annotated prokaryotic genomes having diverse compositional biases. We observed that linear correction was sufficient for recovering signals even at the extremes of these biases. Further comparative genomics studies were made possible upon correction of these signals. We find that the average Euclidian distance between RBS signal frequency matrices of different genomes can be significantly reduced by using the correction technique. Within this reduced average distance, we can find examples of class-specific RBS signals. Our results have implications for motif-based prediction, particularly with regards to the estimation of reliable inter-genomic model parameters.
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影响因子：
5.6
作者：
SCHNEIDER, TD;STORMO, GD;EHRENFEUCHT, A
通讯作者：
EHRENFEUCHT, A
影响因子：
2.1
作者：
MIKKONEN, M;VUORISTO, J;ALATOSSAVA, T
通讯作者：
ALATOSSAVA, T
影响因子：
--
作者：
SHANNON, CE
通讯作者：
SHANNON, CE
影响因子：
--
作者：
SHANNON, CE
通讯作者：
SHANNON, CE
影响因子：
3.2
作者：
Zheng, M;Doan, B;Storz, G
通讯作者：
Storz, G