MotifClick: prediction of cis-regulatory binding sites via merging cliques.
MotifClick: prediction of cis-regulatory binding sites via merging cliques.
复制标题
MotifClick：通过合并派系预测顺式调控结合位点
DOI：
10.1186/1471-2105-12-238
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发表时间：
2011-06-16
影响因子：
3
通讯作者：
Su Z
中科院分区：
文献类型：
--
作者：
Zhang S;Li S;Niu M;Pham PT;Su Z
背景
尽管已经开发了数十种算法和工具来使用各种方法在一组基因间序列中找到一组称为基序的顺式调节结合位点，但这些工具中的大多数专注于识别与其背景序列显著不同的结合位点。然而，一些基序可能具有与其背景序列相似的核苷酸分布。因此，这些工具可能会遗漏这些结合位点。
结果
在这里，我们提出了一个基于图形的多项式时间算法，MotifClick，预测顺式调节结合位点，特别是那些具有相似的核苷酸分布，他们的背景序列。为了找到长度为k的结合位点，我们用输入序列中的一些2（k-1）-mer作为顶点构建一个图，如果两个2（k-1）-mer之间的局部无间隙比对的最大匹配数大于一个截止值，则用一条边连接两个顶点。我们确定一个主题作为一组类似的k-mer从合并组的最大集团与一些顶点。
结论
当在原核生物和真核生物的合成和真实的数据集上进行评估时，MotifClick在预测准确性和平衡预测灵敏度和特异性方面优于现有的领先基序查找工具。特别地，当结合位点的核苷酸分布与其背景序列的核苷酸分布相似时，MotifClick比其他工具更有可能识别结合位点。
Background
Although dozens of algorithms and tools have been developed to find a set of cis-regulatory binding sites called a motif in a set of intergenic sequences using various approaches, most of these tools focus on identifying binding sites that are significantly different from their background sequences. However, some motifs may have a similar nucleotide distribution to that of their background sequences. Therefore, such binding sites can be missed by these tools.
Results
Here, we present a graph-based polynomial-time algorithm, MotifClick, for the prediction of cis-regulatory binding sites, in particular, those that have a similar nucleotide distribution to that of their background sequences. To find binding sites with length k, we construct a graph using some 2(k-1)-mers in the input sequences as the vertices, and connect two vertices by an edge if the maximum number of matches of the local gapless alignments between the two 2(k-1)-mers is greater than a cutoff value. We identify a motif as a set of similar k-mers from a merged group of maximum cliques associated with some vertices.
Conclusions
When evaluated on both synthetic and real datasets of prokaryotes and eukaryotes, MotifClick outperforms existing leading motif-finding tools for prediction accuracy and balancing the prediction sensitivity and specificity in general. In particular, when the distribution of nucleotides of binding sites is similar to that of their background sequences, MotifClick is more likely to identify the binding sites than the other tools.
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