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通过结合探针放置和嵌入实现更好的基因芯片微阵列布局。

Better genechip microarray layouts by combining probe placement and embedding.

作者信息

de Carvalho Sérgio A, Rahmann Sven

机构信息

Computational Methods for Emerging Technologies, Genome Informatics, Technische Fakultät, Bielefeld University, D-33594 Bielefeld, Germany.

出版信息

J Bioinform Comput Biol. 2008 Jun;6(3):623-41. doi: 10.1142/s0219720008003576.

Abstract

The microarray layout problem is a generalization of the border length minimization problem, and asks to distribute oligonucleotide probes on a microarray and to determine their embeddings in the deposition sequence in such a way that the overall quality of the resulting synthesized probes is maximized. Because of its inherent computational complexity, it is traditionally attacked in several phases: partitioning, placement, and re-embedding. We present the first algorithm, Greedy+, that combines placement and embedding and that results in improved layouts in terms of border length and conflict index (a more realistic measure of probe quality), both on arrays of random probes and on existing Affymetrix GeneChip arrays. We also present a detailed study on the layouts of the latest GeneChip arrays, and show how Greedy+ can further improve layout quality by as much as 12% in terms of border length and 35% in terms of conflict index.

摘要

微阵列布局问题是边界长度最小化问题的一种推广,它要求在微阵列上分布寡核苷酸探针,并确定它们在沉积序列中的嵌入方式,以使所得合成探针的整体质量最大化。由于其固有的计算复杂性,传统上它分几个阶段进行处理:划分、布局和重新嵌入。我们提出了第一种算法Greedy+,它将布局和嵌入相结合,并且在随机探针阵列和现有的Affymetrix基因芯片阵列上,在边界长度和冲突指数(一种更实际的探针质量度量)方面都能产生改进的布局。我们还对最新的基因芯片阵列布局进行了详细研究,并展示了Greedy+如何在边界长度方面将布局质量进一步提高多达12%,在冲突指数方面提高35%。

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