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首页> 外文期刊>Computational Biology and Bioinformatics, IEEE/ACM Transactions on >Divide and Conquer Approach to Contact Map Overlap Problem Using 2D-Pattern Mining of Protein Contact Networks
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Divide and Conquer Approach to Contact Map Overlap Problem Using 2D-Pattern Mining of Protein Contact Networks

机译：使用蛋白质接触网络的二维模式挖掘来解决接触图重叠问题的分治法

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摘要

A novel approach to Contact Map Overlap (CMO) problem is proposed using the two dimensional clusters present in the contact maps. Each protein is represented as a set of the non-trivial clusters of contacts extracted from its contact map. The approach involves finding matching regions between the two contact maps using approximate 2D-pattern matching algorithm and dynamic programming technique. These matched pairs of small contact maps are submitted in parallel to a fast heuristic CMO algorithm. The approach facilitates parallelization at this level since all the pairs of contact maps can be submitted to the algorithm in parallel. Then, a merge algorithm is used in order to obtain the overall alignment. As a proof of concept, MSVNS, a heuristic CMO algorithm is used for global as well as local alignment. The divide and conquer approach is evaluated for two benchmark data sets that of Skolnick and Ding et al. It is interesting to note that along with achieving saving of time, better overlap is also obtained for certain protein folds.
机译：提出了一种使用接触图中存在的二维簇来解决接触图重叠（CMO）问题的新方法。每种蛋白质表示为从其接触图中提取的一组非平凡的接触簇。该方法涉及使用近似2D模式匹配算法和动态编程技术在两个接触图之间找到匹配区域。这些匹配的小联系图对与快速启发式CMO算法并行提交。由于可以将所有成对的接触图对并行提交给算法，因此该方法有助于在此级别进行并行化。然后，使用合并算法以获得整体对齐。作为概念验证，启发式CMO算法MSVNS用于全局和局部对齐。分治法是针对Skolnick和Ding等人的两个基准数据集进行评估的。有趣的是，在节省时间的同时，某些蛋白质折叠也获得了更好的重叠。

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