Department of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
J Theor Biol. 2010 Nov 21;267(2):164-70. doi: 10.1016/j.jtbi.2010.08.019. Epub 2010 Aug 20.
In this paper, a new efficient algorithm is presented for haplotype block partitioning based on haplotype diversity. In this algorithm, finding the largest meaningful block that satisfies the diversity condition is the main goal as an optimization problem. The algorithm can be performed in polynomial time complexity with regard to the number of haplotypes and SNPs. We apply our algorithm on three biological data sets from chromosome 21 in three different population data sets from HapMap data bulk; the obtained results show the efficiency and better performance of our algorithm in comparison with three other well known methods.
本文提出了一种基于单倍型多样性的新的高效单倍型块划分算法。在该算法中，找到满足多样性条件的最大有意义块是作为优化问题的主要目标。该算法可以在多项式时间复杂度内处理单倍型和 SNPs 的数量。我们将算法应用于 HapMap 数据集中三个不同人群数据集的 21 号染色体上的三个生物数据集；得到的结果表明，与其他三种知名方法相比，我们的算法具有更高的效率和更好的性能。
