Genomic tiling arrays are a type of DNA microarrays which can investigate the complete genome of arbitrary species for which the sequence is known. The design or selection of suitable oligonucleotide probes for such arrays is however computationally difficult if features such as oligonucleotide quality and repetitive regions are to be considered. We formulate the minimal cost tiling path problem for the selection of oligonucleotides from a set of candidates, which is equivalent to a shortest path problem. An efficient implementation of Dijkstra's shortest path algorithm allows us to compute globally optimal tiling paths from millions of candidate oligonucleotides on a standard desktop computer. The solution to this multi-criterion optimization is spatially adaptive to the problem instance. Our formulation incorporates experimental constraints with respect to specific regions of interest and tradeoffs between hybridization parameters, probe quality and tiling density easily. Solutions for the basic formulation can be obtained more efficiently from Monge theory. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Schliep, A., & Krause, R. (2007). Efficient computational design of tiling arrays using a shortest path approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4645 LNBI, pp. 383–394). Springer Verlag. https://doi.org/10.1007/978-3-540-74126-8_36
Mendeley helps you to discover research relevant for your work.