de Carvalho Ségio A, Rahmann Sven
Computational Methods for Emerging Technologies, Genome Informatics, Technische Fakultät, Bielefeld University, D-33594 Bielefeld, Germany.
Comput Syst Bioinformatics Conf. 2007;6:417-27.
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 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 large-scale study on how the layouts of GeneChip arrays have improved over time, and show how Greedy+ can further improve layout quality by as much as 8% in terms of border length and 34% in terms of conflict index.
微阵列布局问题是边界长度最小化问题的推广,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,传统上它是分几个阶段解决的:划分、布局和重新嵌入。我们提出了第一种算法Greedy+,它结合了布局和嵌入,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)方面都能得到改进的布局。我们还进行了一项大规模研究,探讨基因芯片阵列的布局如何随时间得到改进,并展示了Greedy+如何在边界长度方面进一步将布局质量提高8%,在冲突指数方面提高34%。