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一种用于最小简并引物选择的高效算法。

An efficient algorithm for minimum degeneracy primer selection.

作者信息

Balla Sudha, Rajasekaran Sanguthevar

机构信息

Computer Science and Engineering Department, University of Connecticut, Storrs, CT 06269-2155, USA.

出版信息

IEEE Trans Nanobioscience. 2007 Mar;6(1):12-7. doi: 10.1109/tnb.2007.891895.

Abstract

Selecting degenerate primers for multiplex polymerase chain reaction (MP-PCR) experiments, called the degenerate primer design problem (DPDP), is an important problem in computational molecular biology and has drawn the attention of numerous researchers in the recent past. Several variants of DPDP were formulated by Linhart and Shamir and proven to be NP-complete. A number of algorithms have been proposed for one such variant, namely, the maximum coverage degenerate primer design problem (MC-DPDP). In this paper, we consider another important variant called the minimum degeneracy degenerate primer design with errors problem (MD-DPDEP), propose an algorithm to design a degenerate primer of minimum degeneracy for a given set of DNA sequences and show experimental results of its performance on random and real biological datasets. Our algorithm combines methodologies in motif discovery and an iterative technique to design the primer.

摘要

为多重聚合酶链反应(MP-PCR)实验选择简并引物,即简并引物设计问题(DPDP),是计算分子生物学中的一个重要问题,并且在最近引起了众多研究人员的关注。Linhart和Shamir提出了DPDP的几种变体,并证明它们是NP完全问题。针对其中一种变体,即最大覆盖简并引物设计问题(MC-DPDP),已经提出了许多算法。在本文中,我们考虑另一个重要变体,称为带错误的最小简并度简并引物设计问题(MD-DPDEP),提出一种算法来为给定的一组DNA序列设计具有最小简并度的简并引物,并展示其在随机和真实生物数据集上的性能实验结果。我们的算法结合了基序发现方法和一种迭代技术来设计引物。

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