SeeSite：高效发现共现剪接位点和外显子剪接增强子
SeeSite: Efficiently Finding Co-occurring Splice Sites and Exon Splicing Enhancers
摘要：
识别剪接位点的问题由两个子问题组成：找到它们的边界和表征它们的序列标记。其他剪接元件-包括，增强子和沉默子-出现在内含子和外显子区域在剪接活动中起重要作用。现有的检测剪接元件的方法局限于寻找剪接位点或增强子和沉默子，即使这些元件是众所周知的共同出现。我们介绍了SeeSite，一个高效和准确的工具，用于检测剪接位点及其互补外显子剪接增强子（ESEs）。SeeSite有三个阶段：图构建，寻找密集子图，以及恢复剪接位点和ESE及其共识。第三步是解决带离群点的一致序列，这是一个NP完全的字符串聚类问题。我们证明了我们的算法在多项式时间内输出接近最优的解决方案。使用SeeSite，我们证明了ESEs优先与较弱的剪接位点相关，并且特定规范形式的剪接位点与特定的ESEs共同出现。
英文摘要：
The problem of identifying splice sites consists of two sub-problems: finding their boundaries, and characterizing their sequence markers. Other splicing elements---including, enhancers and silencers---that occur in the intronic and exonic regions play an important role in splicing activity. Existing methods for detecting splicing elements are limited to finding either splice sites or enhancers and silencers, even though these elements are well-known to co-occur. We introduce SeeSite, an efficient and accurate tool for detecting splice sites and their complementary exon splicing enhancers (ESEs). SeeSite has three stages: graph construction, finding dense subgraphs, and recovering splice sites and ESEs along with their consensus. The third step involves solving Consensus Sequence with Outliers, an NP-complete string clustering problem. We prove that our algorithm for this problem outputs near-optimal solutions in polynomial time. Using SeeSite we demonstrate that ESEs are preferentially associated with weaker splice sites, and splice sites of a certain canonical form co-occur with specific ESEs.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
